626 Xgboost Jobs

Description Brief Job Overview The Digital & Innovation group at USP is seeking a Data Scientist with skills in advanced analytics (predictive modeling, machine learning, natural language processing) and data visualization to work on projects that drive innovations and deliver digital solutions. We are seeking someone who understands the power of data and enjoys communicating the insights and help create an unified experience across our ecosystem. How will YOU create impact here at USP? In this role at USP, you contribute to USP's public health mission of increasing equitable access to high-quality, safe medicine and improving global health through public standards and related programs. In addition, as part of our commitment to our employees, Global, People, and Culture, in partnership with the Equity Office, regularly invests in the professional development of all people managers. This includes training in inclusive management styles and other competencies necessary to ensure engaged and productive work environments. Use exploratory data analysis to spot anomalies, understand patterns, test hypotheses, or check assumptions. Apply various ML techniques to perform classification or regression tasks to drive business impact and address identified needs in an agile manner. Use natural language processing techniques to extract information and improve business workflows. Interpret and communicate results clearly and concisely to audiences with varying backgrounds and degrees of technical understanding. Collaborate with other data scientists, data engineers, and IT team to help ensure project delivery and success. Who is USP Looking For? The successful candidate will have a demonstrated understanding of our mission, commitment to excellence through inclusive and equitable behaviors and practices, ability to quickly build credibility with stakeholders, along with the following competencies and experience: Education: Bachelor’s degree in relevant field (e.g. Engineering, Analytics or Data Science, Computer Science, Statistics) or equivalent experience. Experience: Data Scientist: 3 – 6 years of hands-on experience in data science, advanced analytics, machine learning, statistics, and natural language processing Senior Data Scientist: 6 - 10 years of hands-on experience in data science, advanced analytics, machine learning, statistics, and natural language processing Technical proficiency in the following: python/packages: pandas, numpy, regex, scikit-learn, xgboost, and visualization packages (such as matplotlib, seaborn); SQL Proficiency in CNN/ RNN models. Proficiency in using GenAI concepts with graph data. Experience with data extraction and scraping. Experience with XML documents and DOM model. Additional Desired Preferences Master’s degree (Information Systems Management, Analytics, Data Engineering, Sciences, or other Quantitative program) Experience with scientific chemistry nomenclature or prior work experience in life sciences, chemistry, or hard sciences or degree in sciences Experience with pharmaceutical / IQVIA datasets and nomenclature Experience translating stakeholder needs into technical project outputs Experience working with knowledge graphs in conjunction with RAG patterns and Chunking methodologies. Ability to explain complex technical issues to a non-technical audience Self-directed and able to handle multiple concurrent projects and prioritize tasks independently Able to make tough decisions when trade-offs are required to deliver results Strong communication skills required: Verbal, written, and interpersonal Supervisory Responsibilities This is non-supervisory position Benefits USP provides the benefits to protect yourself and your family today and tomorrow. From company-paid time off and comprehensive healthcare options to retirement savings, you can have peace of mind that your personal and financial well-being is protected. Note: USP does not accept unsolicited resumes from 3rd party recruitment agencies and is not responsible for fees from recruiters or other agencies except under specific written agreement with USP. Who is USP? The U.S. Pharmacopeial Convention (USP) is an independent scientific organization that collaborates with the world's top authorities in health and science to develop quality standards for medicines, dietary supplements, and food ingredients. USP's fundamental belief that Equity = Excellence manifests in our core value of Passion for Quality through our more than 1,300 hard-working professionals across twenty global locations to deliver the mission to strengthen the supply of safe, quality medicines and supplements worldwide. At USP, we value inclusivity for all. We recognize the importance of building an organizational culture with meaningful opportunities for mentorship and professional growth. From the standards we create, the partnerships we build, and the conversations we foster, we affirm the value of Diversity, Equity, Inclusion, and Belonging in building a world where everyone can be confident of quality in health and healthcare. USP is proud to be an equal employment opportunity employer (EEOE) and affirmative action employer. We are committed to creating an inclusive environment in all aspects of our work—an environment where every employee feels fully empowered and valued irrespective of, but not limited to, race, ethnicity, physical and mental abilities, education, religion, gender identity, and expression, life experience, sexual orientation, country of origin, regional differences, work experience, and family status. We are committed to working with and providing reasonable accommodation to individuals with disabilities.

About Us: Red & White Education Pvt. Ltd., established in 2008, is Gujarats top NSDC & ISO-certified institute focused on skill-based education and global employability. Role Overview: Were hiring a full-time Onsite AI, Machine Learning, and Data Science Faculty/ Trainer with strong communication skills and a passion for teaching, Key Responsibilities: Deliver high-quality lectures on AI, Machine Learning, and Data Science . Design and update course materials, assignments, and projects. Guide students on hands-on projects, real-world applications, and research work. Provide mentorship and support for student learning and career development. Stay updated with the latest trends and advancements in AI/ML and Data Science. Conduct assessments, evaluate student progress, and provide feedback. Participate in curriculum development and improvements. Skills & Tools: Core Skills: ML, Deep Learning, NLP, Computer Vision, Business Intelligence, AI Model Development, Business Analysis. Programming: Python, SQL (Must), Pandas, NumPy, Excel. ML & AI Tools: Scikit-learn (Must), XGBoost, LightGBM, TensorFlow, PyTorch (Must), Keras, Hugging Face. Data Visualization: Tableau, Power BI (Must), Matplotlib, Seaborn, Plotly. NLP & CV: Transformers, BERT, GPT, OpenCV, YOLO, Detectron2. Advanced AI: Transfer Learning, Generative AI, Business Case Studies. Education & Experience Requirements: Bachelor's/Master’s/Ph.D. in Computer Science, AI, Data Science, or a related field. Minimum 1+ years of teaching or industry experience in AI/ML and Data Science. Hands-on experience with Python, SQL, TensorFlow, PyTorch, and other AI/ML tools. Practical exposure to real-world AI applications, model deployment, and business analytics. For further information, please feel free to contact 7862813693 us via email at career@rnwmultimedia.edu.in Job Types: Full-time, Permanent Pay: ₹30,000.00 - ₹35,000.00 per month Benefits: Flexible schedule Leave encashment Paid sick time Paid time off Provident Fund Schedule: Day shift Supplemental Pay: Performance bonus Yearly bonus Application Question(s): Current Salary? Education: Bachelor's (Required) Experience: Teaching / Mentoring: 1 year (Required) AIML : 1 year (Required) Data science: 1 year (Preferred) Location: Varachha, Surat, Gujarat (Required) Work Location: In person

Job Title: AI/ML Ops Engineer Location: Ahmedabad - Onsite Duration: 2-4 years experinece About the Role We are seeking an experienced AI/ML Ops Engineer to join our team and drive the development, deployment, and operationalization of machine learning and large language model (LLM) systems. You will be responsible for building scalable ML pipelines, enabling intelligent retrieval-augmented generation (RAG) capabilities, and deploying services that power intelligent enterprise applications. Key Responsibilities Develop and maintain machine learning models to forecast user behavior using structured time-series data. Build and optimize end-to-end regression pipelines using advanced libraries such as CatBoost , XGBoost , and LightGBM . Design and implement RAG (Retrieval-Augmented Generation) pipelines for enterprise chatbot systems utilizing tools like LangChain , LLM Router , or custom-built orchestrators. Work with vector databases for semantic document retrieval and reranking. Integrate external APIs into LLM workflows to enable tool/function calling capabilities. Package and deploy ML services using tools such as Docker , FastAPI , or Flask . Collaborate with cross-functional teams to ensure reliable CI/CD deployment and version control practices. Core Technologies & Tools Languages: Python (primary), Bash, SQL ML Libraries: scikit-learn, CatBoost, XGBoost, LightGBM, PyTorch, TensorFlow LLM & RAG Tools: LangChain, Hugging Face Transformers, LlamaIndex, LLM Router Vector Stores: FAISS, Weaviate, Chroma, Pinecone Deployment & APIs: Docker, FastAPI, Flask, Postman Infrastructure & Version Control: Git, GitHub, CI/CD pipelines Preferred Qualifications Proven experience in ML Ops, AI infrastructure, or productionizing ML models. Strong understanding of large-scale ML system design and deployment strategies. Experience working with vector databases and LLM-based applications in production. Job Type: Full-time Pay: Up to ₹75,229.87 per month Benefits: Provident Fund Experience: AI/ML: 3 years (Preferred) ML OPs: 3 years (Preferred) AWS: 1 year (Preferred) Python: 3 years (Preferred) Work Location: In person

About Us: Red & White Education Pvt. Ltd., established in 2008, is Gujarats top NSDC & ISO-certified institute focused on skill-based education and global employability. Role Overview: Were hiring a full-time Onsite AI, Machine Learning, and Data Science Faculty/ Trainer with strong communication skills and a passion for teaching, Key Responsibilities: Deliver high-quality lectures on AI, Machine Learning, and Data Science . Design and update course materials, assignments, and projects. Guide students on hands-on projects, real-world applications, and research work. Provide mentorship and support for student learning and career development. Stay updated with the latest trends and advancements in AI/ML and Data Science. Conduct assessments, evaluate student progress, and provide feedback. Participate in curriculum development and improvements. Skills & Tools: Core Skills: ML, Deep Learning, NLP, Computer Vision, Business Intelligence, AI Model Development, Business Analysis. Programming: Python, SQL (Must), Pandas, NumPy, Excel. ML & AI Tools: Scikit-learn (Must), XGBoost, LightGBM, TensorFlow, PyTorch (Must), Keras, Hugging Face. Data Visualization: Tableau, Power BI (Must), Matplotlib, Seaborn, Plotly. NLP & CV: Transformers, BERT, GPT, OpenCV, YOLO, Detectron2. Advanced AI: Transfer Learning, Generative AI, Business Case Studies. Education & Experience Requirements: Bachelor's/Master’s/Ph.D. in Computer Science, AI, Data Science, or a related field. Minimum 1+ years of teaching or industry experience in AI/ML and Data Science. Hands-on experience with Python, SQL, TensorFlow, PyTorch, and other AI/ML tools. Practical exposure to real-world AI applications, model deployment, and business analytics. For further information, please feel free to contact 7862813693 us via email at career@rnwmultimedia.edu.in Job Types: Full-time, Permanent Pay: ₹30,000.00 - ₹35,000.00 per month Benefits: Flexible schedule Leave encashment Paid sick time Paid time off Provident Fund Schedule: Day shift Supplemental Pay: Performance bonus Yearly bonus Application Question(s): Current Salary? Education: Bachelor's (Required) Experience: Teaching / Mentoring: 1 year (Required) AIML : 1 year (Required) Data science: 1 year (Preferred) Location: Varachha, Surat, Gujarat (Required) Work Location: In person

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. Job Summary Responsible for contributing to the development and deployment of machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms as a part of a larger team. Contributes to translating application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Contributes to developing ways to use machine learning to solve problems and discover new products, working on a portion of the problem and collaborating with more senior researchers as needed. Works with moderate guidance in own area of knowledge. Job Description Core Responsibilities About the Role: We are seeking an experienced Data Scientist to join our growing Operational Intelligence team. You will play a key role in building intelligent systems that help reduce alert noise, detect anomalies, correlate events, and proactively surface operational insights across our large-scale streaming infrastructure. You’ll work at the intersection of machine learning, observability, and IT operations, collaborating closely with Platform Engineers, SREs, Incident Managers, Operators and Developers to integrate smart detection and decision logic directly into our operational workflows. This role offers a unique opportunity to push the boundaries of AI/ML in large-scale operations. We welcome curious minds who want to stay ahead of the curve, bring innovative ideas to life, and improve the reliability of streaming infrastructure that powers millions of users globally. What You’ll Do Design and tune machine learning models for event correlation, anomaly detection, alert scoring, and root cause inference Engineer features to enrich alerts using service relationships, business context, change history, and topological data Apply NLP and ML techniques to classify and structure logs and unstructured alert messages Develop and maintain real-time and batch data pipelines to process alerts, metrics, traces, and logs Use Python, SQL, and time-series query languages (e.g., PromQL) to manipulate and analyze operational data Collaborate with engineering teams to deploy models via API integrations, automate workflows, and ensure production readiness Contribute to the development of self-healing automation, diagnostics, and ML-powered decision triggers Design and validate entropy-based prioritization models to reduce alert fatigue and elevate critical signals Conduct A/B testing, offline validation, and live performance monitoring of ML models Build and share clear dashboards, visualizations, and reporting views to support SREs, engineers, and leadership Participate in incident postmortems, providing ML-driven insights and recommendations for platform improvements Collaborate on the design of hybrid ML + rule-based systems to support dynamic correlation and intelligent alert grouping Lead and support innovation efforts including POCs, POVs, and exploration of emerging AI/ML tools and strategies Demonstrate a proactive, solution-oriented mindset with the ability to navigate ambiguity and learn quickly Participate in on-call rotations and provide operational support as needed Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or a related field 3+ years of experience building and deploying ML solutions in production environments 2+ years working with AIOps, observability, or real-time operations data Strong coding skills in Python (including pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) Experience working with SQL, time-series query languages (e.g., PromQL), and data transformation in pandas or Spark Familiarity with LLMs, prompt engineering fundamentals, or embedding-based retrieval (e.g., sentence-transformers, vector DBs) Strong grasp of modern ML techniques including gradient boosting (XGBoost/LightGBM), autoencoders, clustering (e.g., HDBSCAN), and anomaly detection Experience managing structured + unstructured data, and building features from logs, alerts, metrics, and traces Familiarity with real-time event processing using tools like Kafka, Kinesis, or Flink Strong understanding of model evaluation techniques including precision/recall trade-offs, ROC, AUC, calibration Comfortable working with relational (PostgreSQL), NoSQL (MongoDB), and time-series (InfluxDB, Prometheus) databases Ability to collaborate effectively with SREs, platform teams, and participate in Agile/DevOps workflows Clear written and verbal communication skills to present findings to technical and non-technical stakeholders Comfortable working across Git, Confluence, JIRA, & collaborative agile environments Nice To Have Experience building or contributing to the AIOps platform (e.g., Moogsoft, BigPanda, Datadog, Aisera, Dynatrace, BMC etc.) Experience working in streaming media, OTT platforms, or large-scale consumer services Exposure to Infrastructure as Code (Terraform, Pulumi) and modern cloud-native tooling Working experience with Conviva, Touchstream, Harmonic, New Relic, Prometheus, & event- based alerting tools Hands-on experience with LLMs in operational contexts (e.g., classification of alert text, log summarization, retrieval-augmented generation) Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings-based search for observability data Experience using MLflow, SageMaker, or Airflow for ML workflow orchestration Knowledge of LangChain, Haystack, RAG pipelines, or prompt templating libraries Exposure to MLOps practices (e.g., model monitoring, drift detection, explainability tools like SHAP or LIME) Experience with containerized model deployment using Docker or Kubernetes Use of JAX, Hugging Face Transformers, or LLaMA/Claude/Command-R models in experimentation Experience designing APIs in Python or Go to expose models as services Cloud proficiency in AWS/GCP, especially for distributed training, storage, or batch inferencing Contributions to open-source ML or DevOps communities, or participation in AIOps research/benchmarking efforts Certifications in cloud architecture, ML engineering, or data science specialization Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 2-5 Years

As a Senior Machine Learning Engineer with over 10 years of experience, you will play a crucial role in designing, building, and deploying scalable machine learning systems in production. In this role, you will collaborate closely with data scientists to operationalize models, take ownership of ML pipelines from end to end, and enhance the reliability, automation, and performance of our ML infrastructure. Your primary responsibilities will include designing and constructing robust ML pipelines and services for training, validation, and model deployment. You will work in collaboration with various stakeholders such as data scientists, solution architects, and DevOps engineers to ensure alignment with project goals and requirements. Additionally, you will be responsible for ensuring cloud integration compatibility with AWS and Azure, building reusable infrastructure components following best practices in DevOps and MLOps, and adhering to security standards and regulatory compliance. To excel in this role, you should possess strong programming skills in Python, have deep experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn, and be proficient in MLOps tools like MLflow, Airflow, TFX, Kubeflow, or BentoML. Experience in deploying models using Docker and Kubernetes, familiarity with cloud platforms and ML services, and proficiency in data engineering tools are essential for success in this position. Additionally, knowledge of CI/CD, version control, and infrastructure as code along with experience in monitoring/logging tools will be advantageous. Good-to-have skills include experience with feature stores and experiment tracking platforms, knowledge of edge/embedded ML, model quantization, and optimization, as well as familiarity with model governance, security, and compliance in ML systems. Exposure to on-device ML or streaming ML use cases and experience in leading cross-functional initiatives or mentoring junior engineers will also be beneficial. Joining Ericsson will provide you with an exceptional opportunity to leverage your skills and creativity to address some of the world's toughest challenges. You will be part of a diverse team of innovators who are committed to pushing the boundaries of innovation and crafting groundbreaking solutions. As a member of this team, you will be challenged to think beyond conventional limits and contribute to shaping the future of technology.,

As an AI / ML Engineer, you will be responsible for utilizing your expertise in the field of Artificial Intelligence and Machine Learning to develop innovative solutions. You should hold a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, Mathematics, or a related field. With a minimum of 6 years of experience in AI/ML, you are expected to demonstrate proficiency in Python and various ML libraries such as scikit-learn, XGBoost, pandas, NumPy, matplotlib, and seaborn. In this role, you will need a strong understanding of machine learning algorithms and deep learning architectures including CNNs, RNNs, and Transformers. Hands-on experience with TensorFlow, PyTorch, or Keras is essential. You should also have expertise in data preprocessing, feature selection, exploratory data analysis (EDA), and model interpretability. Additionally, familiarity with API development and deploying models using frameworks like Flask, FastAPI, or similar tools is required. Experience with MLOps tools such as MLflow, Kubeflow, DVC, and Airflow will be beneficial. Knowledge of cloud platforms like AWS (SageMaker, S3, Lambda), GCP (Vertex AI), or Azure ML is preferred. Proficiency in version control using Git, CI/CD processes, and containerization with Docker is essential for this role. Bonus skills that would be advantageous include familiarity with NLP frameworks (e.g., spaCy, NLTK, Hugging Face Transformers), Computer Vision experience using OpenCV or YOLO/Detectron, and knowledge of Reinforcement Learning or Generative AI (GANs, LLMs). Experience with vector databases such as Pinecone or Weaviate, as well as LangChain for AI agent building, is a plus. Familiarity with data labeling platforms and annotation workflows will also be beneficial. In addition to technical skills, you should possess soft skills such as an analytical mindset, strong problem-solving abilities, effective communication, and collaboration skills. The ability to work independently in a fast-paced, agile environment is crucial. A passion for AI/ML and a proactive approach to staying updated with the latest developments in the field are highly desirable for this role.,

Data Science (GenAI & Prompt engineering) – Bangalore Business Analytics Analyst 2 About CITI Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We have 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. Analytics and Information Management (AIM) Citi AIM was established in 2003, and is located across multiple cities in India – Bengaluru, Chennai, Pune and Mumbai. It is a global community that objectively connects and analyzes information, to create actionable intelligence for our business leaders. It identifies fact-based opportunities for revenue growth in partnership with the businesses. The function balances customer needs, business strategy, and profit objectives using best in class and relevant analytic methodologies. What do we do? The North America Consumer Bank – Data Science and Modeling team analyzes millions of prospects and billions of customer level transactions using big data tools and machine learning, AI techniques to unlock opportunities for our clients in meeting their financial needs and create economic value for the bank. The team extracts relevant insights, identifies business opportunities, converts business problems into modeling framework, uses big data tools, latest deep learning and machine learning algorithms to build predictive models, implements solutions and designs go-to-market strategies for a huge variety of business problems. Role Description The role will be Business Analytics Analyst 2 in the Data Science and Modeling of North America Consumer Bank team The role will report to the AVP / VP leading the team What do we offer: The Next Gen Analytics (NGA) team is a part of the Analytics & Information Management (AIM) unit. The NGA modeling team will focus on the following areas of work: Role Expectations: Client Obsession – Create client centric analytic solution to business problems. Individual should be able to have a holistic view of multiple businesses and develop analytic solutions accordingly. Analytic Project Execution – Own and deliver multiple and complex analytic projects. This would require an understanding of business context, conversion of business problems in modeling, and implementing such solutions to create economic value. Domain expert – Individuals are expected to be domain expert in their sub field, as well as have a holistic view of other business lines to create better solutions. Key fields of focus are new customer acquisition, existing customer management, customer retention, product development, pricing and payment optimization and digital journey. Modeling and Tech Savvy – Always up to date with the latest use cases of modeling community, machine learning and deep learning algorithms and share knowledge within the team. Statistical mind set – Proficiency in basic statistics, hypothesis testing, segmentation and predictive modeling. Communication skills – Ability to translate and articulate technical thoughts and ideas to a larger audience including influencing skills with peers and senior management. Strong project management skills. Ability to coach and mentor juniors. Contribute to organizational initiatives in wide ranging areas including competency development, training, organizational building activities etc. Role Responsibilities: Work with large and complex datasets using a variety of tools (Python, PySpark, SQL, Hive, etc.) and frameworks to build Deep learning/generative AI solutions for various business requirements. Primary focus areas include model training/fine-tuning, model validation, model deployment, and model governance related to multiple portfolios. Design, fine-tune and implement LLMs/GenAI applications using techniques like prompt engineering, Retrieval Augmented Generation (RAG) and model fine-tuning Responsible for documenting data requirements, data collection/processing/cleaning, and exploratory data analysis, including utilizing deep learning /generative AI algorithms and, data visualization techniques. Incumbents in this role may often be referred to as Data Scientists. Specialization in marketing, risk, digital, and AML fields possible, applying Deep learning & generative AI models to innovate in these domains. Collaborate with team members and business partners to build model-driven solutions using cutting-edge Generative AI models (e.g., Large Language Models) and also at times, ML/traditional methods (XGBoost, Linear, Logistic, Segmentation, etc.) Work with model governance & fair lending teams to ensure compliance of models in accordance with Citi standards. Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules, and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency. What do we look for: If you are a bright and talented individual looking for a career in AI and Machine Learning with a focus on Generative AI , Citi has amazing opportunities for you. Bachelor’s Degree with atleast 3 years of experience in data analytics, or Master’s Degree with 2 years of experience in data analytics, or PhD. Technical Skills Hands-on experience in PySpark/Python/R programing along with strong experience in SQL. 2-4 years of experience working on deep learning, and generative AI applications Experience working on Transformers/ LLMs (OpenAI, Claude, Gemini etc.,), Prompt engineering, RAG based architectures and relevant tools/frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LlamaIndex etc., Solid understanding of deep learning, transformers/language models. Familiarity with vector databases and fine-tuning techniques Experience working with large and multiple datasets, data warehouses and ability to pull data using relevant programs and coding. Strong background in Statistical Analysis. Capability to validate/maintain deployed models in production Self-motivated and able to implement innovative solutions at fast pace Experience in Credit Cards and Retail Banking is preferred Competencies Strong communication skills Multiple stake holder management Strong analytical and problem solving skills Excellent written and oral communication skills Strong team player Control orientated and Risk awareness Working experience in a quantitative field Willing to learn and can-do attitude Ability to build partnerships with cross-function leaders Education: Bachelor's / master’s degree in economics / Statistics / Mathematics / Information Technology / Computer Applications / Engineering etc. from a premier institute Other Details Employment: Full Time Industry: Credit Cards, Retail Banking, Financial Services, Banking ------------------------------------------------------ Job Family Group: Decision Management ------------------------------------------------------ Job Family: Specialized Analytics (Data Science/Computational Statistics) ------------------------------------------------------ Time Type: ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi’s EEO Policy Statement and the Know Your Rights poster.

Description Who is USP? The U.S. Pharmacopeial Convention (USP) is an independent scientific organization that collaborates with the world's top authorities in health and science to develop quality standards for medicines, dietary supplements, and food ingredients. USP's fundamental belief that Equity = Excellence manifests in our core value of Passion for Quality through our more than 1,300 hard-working professionals across twenty global locations to deliver the mission to strengthen the supply of safe, quality medicines and supplements worldwide. At USP, we value inclusivity for all. We recognize the importance of building an organizational culture with meaningful opportunities for mentorship and professional growth. From the standards we create, the partnerships we build, and the conversations we foster, we affirm the value of Diversity, Equity, Inclusion, and Belonging in building a world where everyone can be confident of quality in health and healthcare. USP is proud to be an equal employment opportunity employer (EEOE) and affirmative action employer. We are committed to creating an inclusive environment in all aspects of our work—an environment where every employee feels fully empowered and valued irrespective of, but not limited to, race, ethnicity, physical and mental abilities, education, religion, gender identity, and expression, life experience, sexual orientation, country of origin, regional differences, work experience, and family status. We are committed to working with and providing reasonable accommodation to individuals with disabilities. Brief Job Overview The Digital & Innovation group at USP is seeking a Data Scientist with skills in advanced analytics (predictive modeling, machine learning, natural language processing) and data visualization to work on projects that drive innovations and deliver digital solutions. We are seeking someone who understands the power of data and enjoys communicating the insights and help create an unified experience across our ecosystem. How will YOU create impact here at USP? In this role at USP, you contribute to USP's public health mission of increasing equitable access to high-quality, safe medicine and improving global health through public standards and related programs. In addition, as part of our commitment to our employees, Global, People, and Culture, in partnership with the Equity Office, regularly invests in the professional development of all people managers. This includes training in inclusive management styles and other competencies necessary to ensure engaged and productive work environments. Use exploratory data analysis to spot anomalies, understand patterns, test hypotheses, or check assumptions. Apply various ML techniques to perform classification or regression tasks to drive business impact and address identified needs in an agile manner. Use natural language processing techniques to extract information and improve business workflows. Interpret and communicate results clearly and concisely to audiences with varying backgrounds and degrees of technical understanding. Collaborate with other data scientists, data engineers, and IT team to help ensure project delivery and success. Who is USP Looking For? Education The successful candidate will have a demonstrated understanding of our mission, commitment to excellence through inclusive and equitable behaviors and practices, ability to quickly build credibility with stakeholders, along with the following competencies and experience: Bachelor’s degree in relevant field (e.g. Engineering, Analytics or Data Science, Computer Science, Statistics) or equivalent experience. Experience Data Scientist: 3 – 6 years of hands-on experience in data science, advanced analytics, machine learning, statistics, and natural language processing Senior Data Scientist: 6 - 10 years of hands-on experience in data science, advanced analytics, machine learning, statistics, and natural language processing Technical proficiency in the following: python/packages: pandas, numpy, regex, scikit-learn, xgboost, and visualization packages (such as matplotlib, seaborn); SQL Proficiency in CNN/ RNN models. Proficiency in using GenAI concepts with graph data. Experience with data extraction and scraping. Experience with XML documents and DOM model. Additional Desired Preferences Master’s degree (Information Systems Management, Analytics, Data Engineering, Sciences, or other Quantitative program) Experience with scientific chemistry nomenclature or prior work experience in life sciences, chemistry, or hard sciences or degree in sciences Experience with pharmaceutical / IQVIA datasets and nomenclature Experience translating stakeholder needs into technical project outputs Experience working with knowledge graphs in conjunction with RAG patterns and Chunking methodologies. Ability to explain complex technical issues to a non-technical audience Self-directed and able to handle multiple concurrent projects and prioritize tasks independently Able to make tough decisions when trade-offs are required to deliver results Strong communication skills required: Verbal, written, and interpersonal Supervisory Responsibilities This is non-supervisory position Benefits USP provides the benefits to protect yourself and your family today and tomorrow. From company-paid time off and comprehensive healthcare options to retirement savings, you can have peace of mind that your personal and financial well-being is protected. Note: USP does not accept unsolicited resumes from 3rd party recruitment agencies and is not responsible for fees from recruiters or other agencies except under specific written agreement with USP. Job Category Information Technology Job Type Full-Time

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. Job Summary Responsible for developing and deploying machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms. Translates application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Develops novel ways to use machine learning to solve problems and discover new products. Has in-depth experience, knowledge and skills in own discipline. Usually determines own work priorities. Acts as resource for colleagues with less experience. Job Description About the Role: We are seeking an experienced Data Scientist to join our growing Operational Intelligence team. You will play a key role in building intelligent systems that help reduce alert noise, detect anomalies, correlate events, and proactively surface operational insights across our large-scale streaming infrastructure. You’ll work at the intersection of machine learning, observability, and IT operations, collaborating closely with Platform Engineers, SREs, Incident Managers, Operators and Developers to integrate smart detection and decision logic directly into our operational workflows. This role offers a unique opportunity to push the boundaries of AI/ML in large-scale operations. We welcome curious minds who want to stay ahead of the curve, bring innovative ideas to life, and improve the reliability of streaming infrastructure that powers millions of users globally. What You’ll Do Design and tune machine learning models for event correlation, anomaly detection, alert scoring, and root cause inference Engineer features to enrich alerts using service relationships, business context, change history, and topological data Apply NLP and ML techniques to classify and structure logs and unstructured alert messages Develop and maintain real-time and batch data pipelines to process alerts, metrics, traces, and logs Use Python, SQL, and time-series query languages (e.g., PromQL) to manipulate and analyze operational data Collaborate with engineering teams to deploy models via API integrations, automate workflows, and ensure production readiness Contribute to the development of self-healing automation, diagnostics, and ML-powered decision triggers Design and validate entropy-based prioritization models to reduce alert fatigue and elevate critical signals Conduct A/B testing, offline validation, and live performance monitoring of ML models Build and share clear dashboards, visualizations, and reporting views to support SREs, engineers and leadership Participate in incident postmortems, providing ML-driven insights and recommendations for platform improvements Collaborate on the design of hybrid ML + rule-based systems to supportnamic correlation and intelligent alert grouping Lead and support innovation efforts including POCs, POVs, and explorationemerging AI/ML tools and strategies Demonstrate a proactive, solution-oriented mindset with the ability to navigate ambiguity and learn quickly Participate in on-call rotations and provide operational support as needed Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or a related field 5+ years of experience building and deploying ML solutions in production environments 2+ years working with AIOps, observability, or real-time operations data Strong coding skills in Python (including pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) Experience working with SQL, time-series query languages (e.g., PromQL), and data transformation in pandas or Spark Familiarity with LLMs, prompt engineering fundamentals, or embedding-based retrieval (e.g., sentence-transformers, vector DBs) Strong grasp of modern ML techniques including gradient boosting (XGBoost/LightGBM), autoencoders, clustering (e.g., HDBSCAN), and anomaly detection Experience managing structured + unstructured data, and building features from logs, alerts, metrics, and traces Familiarity with real-time event processing using tools like Kafka, Kinesis, or Flink Strong understanding of model evaluation techniques including precision/recall trade-offs, ROC, AUC, calibration Comfortable working with relational (PostgreSQL), NoSQL (MongoDB), and time-series (InfluxDB, Prometheus) databases Ability to collaborate effectively with SREs, platform teams, and participate in Agile/DevOps workflows Clear written and verbal communication skills to present findings to technical and non-technical stakeholders Comfortable working across Git, Confluence, JIRA, & collaborative agile environments Nice To Have Experience building or contributing to the AIOps platform (e.g., Moogsoft, BigPanda, Datadog, Aisera, Dynatrace, BMC etc.) Experience working in streaming media, OTT platforms, or large-scale consumer services Exposure to Infrastructure as Code (Terraform, Pulumi) and modern cloud-native tooling Working experience with Conviva, Touchstream, Harmonic, New Relic, Prometheus, & event- based alerting tools Hands-on experience with LLMs in operational contexts (e.g., classification of alert text, log summarization, retrieval-augmented generation) Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings-based search for observability data Experience using MLflow, SageMaker, or Airflow for ML workflow orchestration Knowledge of LangChain, Haystack, RAG pipelines, or prompt templating libraries Exposure to MLOps practices (e.g., model monitoring, drift detection, explainability tools like SHAP or LIME) Experience with containerized model deployment using Docker or Kubernetes Use of JAX, Hugging Face Transformers, or LLaMA/Claude/Command-R models in experimentation Experience designing APIs in Python or Go to expose models as services Cloud proficiency in AWS/GCP, especially for distributed training, storage, or batch inferencing Contributions to open-source ML or DevOps communities, or participation in AIOps research/benchmarking efforts. Certifications in cloud architecture, ML engineering, or data science specializations, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations and reports. Contributes to the company by creating patents, Application Programming Interfaces (APIs). Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 5-7 Years

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you'll do You will play an important role in applying and implementing effective machine learning solutions, with a significant focus on Generative AI. You will work with product and engineering teams to contribute to data-driven product strategies, explore and implement GenAI applications, and deliver impactful insights. This positionis an individual contributor role reporting to the Senior Manager, Data Science. Responsibility Experiment with, apply, and implement DL/ML models, with a strong emphasis on Large Language Models (LLMs), Agentic Frameworks, and other Generative AI techniques to predict user behavior, enhance product features, and improve automation Utilize and adapt various GenAI techniques (e.g., prompt engineering, RAG, fine-tuning existing models) to derive actionable insights, generate content, or create novel user experiences Collaborate with product, engineering, and other teams (e.g., Sales, Marketing, Customer Success) to build Agentic system to run campaigns at-scale Conduct in-depth analysis of customer data, market trends, and user insights to inform the development and improvement of GenAI-powered solutions Partner with product teams to design, administer, and analyze the results of A/B and multivariate tests, particularly for GenAI-driven features Leverage data to develop actionable analytical insights & present findings, including the performance and potential of GenAI models, to stakeholders and team members Communicate models, frameworks (especially those related to GenAI), analysis, and insights effectively with stakeholders and business partners Stay updated on the latest advancements in Generative AI and propose their application to relevant business problems Complete assignments with a sense of urgency and purpose, identify and help resolve roadblocks, and collaborate with cross-functional team members on GenAI initiatives Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What you bring Basic Bachelor's or Master's degree in Computer Science, Physics, Mathematics, Statistics, or a related field 3+ years of hands-on experience in building data science applications and machine learning pipelines, with demonstrable experience in Generative AI projects Experience with Python for research and software development purposes, including common GenAI libraries and frameworks Experience with or exposure to prompt engineering, and utilizing pre-trained LLMs (e.g., via APIs or open-source models) Experience with large datasets, distributed computing, and cloud computing platforms (e.g., AWS, Azure, GCP) Proficiency with relational databases (e.g., SQL) Experience in training, evaluating, and deploying machine learning models in production environments, with an interest in MLOps for GenAI Proven track record in contributing to ML/GenAI projects from ideation through to deployment and iteration Experience using machine learning and deep learning algorithms like CatBoost, XGBoost, LGBM, Feed Forward Networks for classification, regression, and clustering problems, and an understanding of how these can complement GenAI solutions Experience as a Data Scientist, ideally in the SaaS domain with some focus on AI-driven product features Preferred PhD in Statistics, Computer Science, or Engineering with specialization in machine learning, AI, or Statistics, with research or projects in Generative AI 5+ years of prior industry experience, with at least 1-2 years focused on GenAI applications Previous experience applying data science and GenAI techniques to customer success, product development, or user experience optimization Hands-on experience with fine-tuning LLMs or working with RAG methodologies Experience with or knowledge of experimentation platforms (like DataRobot) and other AI related ones (like CrewAI) Experience with or knowledge of the software development lifecycle/agile methodology, particularly in AI product development Experience with or knowledge of Github, JIRA/Confluence Contributions to open-source GenAI projects or a portfolio of GenAI related work Programming Languages like Python, SQL; familiarity with R Strong knowledge of common machine learning, deep learning, and statistics frameworks and concepts, with a specific understanding of Large Language Models (LLMs), transformer architectures, and their applications Ability to break down complex technical concepts (including GenAI) into simple terms to present to diverse, technical, and non-technical audiences Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Applicant and Candidate Privacy Notice

We’re Hiring: Machine Learning Engineer (Part-Time | Flexible Remote) Are you an experienced ML Engineer looking for a flexible, part-time opportunity to work on real-world impact projects? Join us in building intelligent systems that match candidates to projects using structured skills, assessments, and feedback data. This is your chance to own end-to-end ML pipelines and work on meaningful automation in the HRTech space — all on your own schedule. 🔍 Role Overview: We’re looking for an ML Engineer to architect and deploy predictive models that power candidate–project matching intelligence , leveraging structured applicant data. You'll design scalable ML workflows and inference pipelines on AWS . 🔧 Key Responsibilities: Build data pipelines to ingest & preprocess applicant data (skills, assessments, feedback) Engineer task-specific features and transformation logic Train predictive models (logistic regression, XGBoost, etc.) on SageMaker Automate batch ETL, retraining flows, and storage with AWS S3 Deploy inference endpoints with Lambda , and integrate with systems in production Monitor model drift, performance, and feedback loops for continuous learning Document architecture, workflows, and ensure explainability ✅ You’ll Need: 4–6+ years in ML/AI engineering roles Strong command of Python, scikit-learn, XGBoost , and feature engineering Proven experience with AWS ML stack : SageMaker, Lambda, S3 Hands-on SQL/NoSQL and automated data workflows Familiarity with CI/CD for ML (CodePipeline, CodeBuild, etc.) Ability to independently own schema, features, and model delivery Bachelor’s or Master’s in CS, Engineering, or related field ⭐ Bonus Points For: NLP experience (extracting features from feedback/comments) Familiarity with serverless architectures Background in recruitment, talent platforms, or skills-matching system 👉 Apply now or DM us to know more. #Hiring #MachineLearning #MLJobs #RemoteJobs #PartTime #AWS #HRTech #MLOps #AI #RecruitmentTech #SageMaker #FlexibleWork

As an expectation a fitting candidate must have/be: Ability to analyze business problem and cut through the data challenges. Ability to churn the raw corpus and develop a data/ML model to provide business analytics (not just EDA), machine learning based document processing and information retrieval Quick to develop the POCs and transform it to high scale production ready code. Experience in extracting data through complex unstructured documents using NLP based technologies. Good to have : Document analysis using Image processing/computer vision and geometric deep learning Technology Stack: Python as a primary programming language. Conceptual understanding of classic ML/DL Algorithms like Regression, Support Vectors, Decision tree, Clustering, Random Forest, CART, Ensemble, Neural Networks, CNN, RNN, LSTM etc. Programming: Must Have: Must be hands-on with data structures using List, tuple, dictionary, collections, iterators, Pandas, NumPy and Object-oriented programming Good to have: Design patterns/System design, cython ML libraries: Must Have: Scikit-learn, XGBoost, imblearn, SciPy, Gensim Good to have: matplotlib/plotly, Lime/sharp Data extraction and handling: Must Have: DASK/Modin, beautifulsoup/scrappy, Multiprocessing Good to have: Data Augmentation, Pyspark, Accelerate NLP/Text analytics: Must Have: Bag of words, text ranking algorithm, Word2vec, language model, entity recognition, CRF/HMM, topic modelling, Sequence to Sequence Good to have: Machine comprehension, translation, elastic search Deep learning: Must Have: TensorFlow/PyTorch, Neural nets, Sequential models, CNN, LSTM/GRU/RNN, Attention, Transformers, Residual Networks Good to have: Knowledge of optimization, Distributed training/computing, Language models Software peripherals: Must Have: REST services, SQL/NoSQL, UNIX, Code versioning Good to have: Docker containers, data versioning Research: Must Have: Well verse with latest trends in ML and DL area. Zeal to research and implement cutting areas in AI segment to solve complex problems Good to have: Contributed to research papers/patents and it is published on internet in ML and DL Morningstar is an equal opportunity employer. Morningstar’s hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We’ve found that we’re at our best when we’re purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you’ll have tools and resources to engage meaningfully with your global colleagues. I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity

Experience Required: 4-7 years Education Qualification: BE/ B. Tech, MCA, MSc (Statistics), MBA from Recognized University Job Description We are looking for a Data Scientist to join our Data Science team. Data science drives all the products we develop. Our products are designed for small to mid-size financial institutions to help them create strategies based on data. The team is responsible for working on predictive model use cases and working closely with technical and functional stakeholders in an agile environment. Role & Responsibilities 3-6 years of relevant work experience in the Data Science/Analytics domain Work with the data scientists’ team, and data engineers. Take ownership of end-to-end data science projects, including problem formulation, data exploration, feature engineering, model development, validation, and deployment, ensuring high-quality deliverables that meet project objectives. Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques. Collaborate with data architects and software engineers to enable deployment of sciences and technologies that will scale across the company’s ecosystem. Responsible for the conception, planning, and prioritizing of data projects Provide support to inexperienced analysts with high-level expertise in an open-source language (e.g., R, Python, etc.) Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown) Utilize data visualization tools (Power BI) to deliver insights to stakeholders. Competencies and Technical Skills Degree holder in computer science or related discipline Proficiency in SQL and database querying for data extraction and manipulation. Proficiency in programming languages such as Python/R, and experience with data manipulation and analysis libraries (e.g., NumPy, pandas, scikit-learn). Familiarity with data visualization tools (e.g., Tableau, Power BI) and proficiency in presenting complex data visually. Solid understanding of experimental design, A/B testing, and statistical hypothesis testing. Proven hands-on experience with machine learning algorithms and parameter tuning, including Ensemble methods (Random Forest, XGBoost), Logistic Regression, Support Vector Machines (SVM), and clustering techniques (e.g., K-Means, DBSCAN). Familiarity with Generative AI concepts and AI Agents is a plus. Excellent verbal and written communication skills, with the ability to effectively convey complex concepts to both technical and non-technical stakeholders· Experience with Snowflake is not necessary but preferable.

Genpact (NYSE: G) is a global professional services and solutions firm dedicated to shaping the future by delivering impactful outcomes. With a team of over 125,000 professionals spread across more than 30 countries, we are characterized by our inherent curiosity, entrepreneurial spirit, and commitment to creating enduring value for our clients. Fueled by our overarching purpose of continually striving towards a world that functions better for individuals, we partner with and enhance leading enterprises, including members of the prestigious Fortune Global 500. Our core competencies revolve around in-depth business and industry expertise, digital operational services, and proficiency in data, technology, and AI. We are currently seeking applications for the position of Business Analyst - Data Scientist to join our dynamic team. As a Business Analyst - Data Scientist at Genpact, you will play a pivotal role in the development and implementation of NLP (Natural Language Processing) models and algorithms, extracting actionable insights from textual data, and collaborating with cross-functional teams to deliver innovative AI solutions. **Responsibilities:** **Model Development:** - Proficiency in various statistical, machine learning, and ensemble algorithms. - Strong understanding of time series algorithms and forecasting use cases. - Ability to discern the strengths and weaknesses of different models and select appropriate ones for specific problems. - Proficiency in evaluating metrics and recommending suitable evaluation metrics for different problem types. **Data Analysis:** - Extracting meaningful insights from structured data. - Preprocessing data for machine learning/artificial intelligence applications. **Collaboration:** - Close collaboration with data scientists, engineers, and business stakeholders. - Providing technical guidance and mentorship to team members. **Integration and Deployment:** - Integrating machine learning models into production systems. - Implementing CI/CD pipelines for continuous integration and deployment. **Documentation and Training:** - Documenting processes, models, and results. - Providing training and support to stakeholders on NLP techniques and tools. **Qualifications we seek in you:** **Minimum Qualifications / Skills:** - Bachelor's degree in computer science, engineering, or a related field. - Proficient programming skills in Python and R. - Experience with data science frameworks such as SKLEARN and NUMPY. - Knowledge of machine learning concepts and frameworks like TensorFlow and PyTorch. - Strong problem-solving and analytical capabilities. - Excellent communication and collaboration skills. **Preferred Qualifications/Skills:** - Experience in predictive analytics and machine learning techniques. - Proficiency in Python/R or any other open-source programming language. - Building and implementing models, using algorithms, and running simulations with various tools. - Familiarity with visualization tools such as Tableau, Power BI, Qlikview, etc. - Proficiency in applied statistics skills, including distributions, statistical testing, regression, etc. - Knowledge and experience in various tools and techniques like forecasting, linear regression, logistic regression, machine learning algorithms (e.g., Random Forest, Gradient Boosting, SVM, XGBoost, Deep Learning), etc. - Experience with big data technologies (Hadoop, Spark). - Familiarity with cloud platforms like AWS, Azure, GCP. **Job Details:** **Title:** Business Analyst - Data Scientist **Primary Location:** India-Hyderabad **Education Level:** Bachelor's / Graduation / Equivalent **Job Posting:** Apr 1, 2025, 2:47:23 AM **Unposting Date:** May 1, 2025, 1:29:00 PM **Master Skills List:** Digital **Job Category:** Full Time,

Job Title: Consultant – Analytics (Full-Time) Location: Ahmedabad or Gurgaon (Hybrid) About The Role Join EXL’s Analytics team as an Analyst or Consultant and play a key role in shaping data-driven marketing strategies for U.S. clients. In this role, you will dive deep into data, build predictive models, perform campaign analytics, and deliver actionable insights that drive measurable business outcomes. This opportunity is ideal for early to mid-career professionals looking to deepen their expertise in marketing analytics, predictive modeling, and data storytelling within a dynamic and collaborative environment. Key Responsibilities Develop predictive models and segmentation frameworks to optimize direct marketing Perform campaign analytics, including performance measurement, deep-dive analyses, and post-campaign evaluations Translate complex business challenges into clear, data-driven solutions Prepare and present client-ready insights to stakeholders Collaborate across teams to support data-driven decision-making Ensure timely delivery of high-quality analytical outputs Skills & Qualifications Bachelor’s or Master’s degree with 2+ years of relevant analytics experience Prior experience in the U.S. Insurance domain is a strong plus Proficiency in Python, SAS, Excel, SQL, and PowerPoint Experience with Tableau, PowerBI, or R is a plus but not mandatory Solid grasp of key ML techniques such as regression, decision trees and ensemble methods like XGBoost Strong communication skills with the ability to simplify complex findings Detail-oriented, self-driven, and eager to thrive in a fast-paced environment

We are seeking a Data Scientist with a strong background in enterprise-scale machine learning, deep expertise in LLMs and Generative AI, and a clear understanding of the evolving Agentic AI ecosystemThe ideal candidate has hands-on experience developing predictive models, recommendation systems, and LLM-powered solutions, and is passionate about leveraging cutting-edge AI to solve complex enterprise challenges. This role will involve working closely with product, engineering, and business teams to design, build, and deploy impactful AI solutions that are both technically robust and business-aligned. The Core Responsibilities For The Job Include The Following ML and Predictive Systems Development: Design, develop, and deploy enterprise-grade machine learning models for recommendations, predictions, and personalization use cases. Work on problems such as churn prediction, intelligent routing, anomaly detection, and behavior modeling. Leverage techniques in supervised, unsupervised, and reinforcement learning as needed based on business context. LLMs And Generative AI Build and fine-tune LLM-based solutions (e. g., GPT, LLaMA, Claude, or open-source models) for tasks such as summarization, semantic search, document understanding, and copilots. Deliver production-ready GenAI projects, applying techniques like RAG (Retrieval-Augmented Generation), prompt engineering, fine-tuning, and vector search (e. g., FAISS, Pinecone, Weaviate). Collaborate with engineering to embed LLM workflows into enterprise applications, ensuring scalability and performance. Agentic AI And Ecosystem Engagement Contribute thought leadership and experimentation around Agentic AI architectures, task orchestration, memory management, tool integration, and decision autonomy. Stay ahead of trends in the open-source and commercial LLM/AI space, including LangChain, AutoGen, DSPy, and ADK-based systems. Develop internal PoCs or evaluate frameworks to assess viability for enterprise use. Collaboration And Delivery Work with cross-functional teams to identify AI opportunities and define technical roadmaps. Translate business needs into data science problems, define success metrics, and communicate results to stakeholders. Ensure model governance, monitoring, and explainability for AI systems in production. Requirements Master's or PhD in Computer Science, Data Science, Statistics, or related field. 5-8 years of experience in data science and ML, with strong enterprise project delivery experience. Proven success in building and deploying ML models and recommendation systems at scale. 2+ projects delivered involving LLMs and Generative AI, with hands-on experience in one or more of: OpenAI, Hugging Face Transformers, LangChain, Vector DBs, or model fine-tuning. Advanced Python programming skills and experience with ML libraries (e. g., Scikit-learn, XGBoost, PyTorch, TensorFlow). Experience with cloud-based ML/AI platforms (e. g., Vertex AI, AWS SageMaker, Azure ML). Strong understanding of system architecture, APIs, data pipelines, and model integration patterns. Preferred Qualifications Experience with Agentic AI frameworks and orchestration systems (LangChain, AutoGen, ADK, CrewAI). Familiarity with prompt optimization, tool chaining, task planning, and autonomous agents. Working knowledge of MLOps best practices, including model versioning, CI/CD for ML, and model monitoring. Strong communication skills and ability to advocate for AI-driven solutions across technical and non-technical teams. Regular follower of AI research, open-source trends, and GenAI product developments. This job was posted by Akshay Kumar Arumulla from Softility.

Introduction A career in IBM Consulting embraces long-term relationships and close collaboration with clients across the globe. In this role, you will work for IBM BPO, part of Consulting that, accelerates digital transformation using agile methodologies, process mining, and AI-powered workflows. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio, including IBM Software and Red Hat. Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be supported by mentors and coaches who will encourage you to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in groundbreaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and learning opportunities in an environment that embraces your unique skills and experience. Your Role And Responsibilities We are seeking for a passionate and skilled Python AI Engineer to design, develop and maintain hybrid AI Platform across multi-cloud and on-premises. Build an AI platform that enables real time machine learning and GenAI at scale along with governance and security frameworks. You will collaborate with data engineer, product managers, and software engineers to bring AI-driven products and features to life. Job Description Work with frameworks like TensorFlow/PyTorch, Scikit-learn, or similar. Design and implement AI/ML models and algorithms using Python3. Develop and maintain scalable, production-grade machine learning pipelines. Conduct data exploration, preprocessing, feature engineering, and model evaluation. Optimize models for performance and scalability in production environments. Collaborate with cross-functional teams to integrate AI components into real-world applications. Stay up to date with the latest research and industry trends in AI and machine learning. Document experiments, code, and processes for reproducibility and transparency. Preferred Education Master's Degree Required Technical And Professional Expertise Strong programming skills in Python 3. Solid understanding of machine learning fundamentals (classification, regression, clustering, etc.). Experience with ML libraries and frameworks (e.g., Scikit-learn, TensorFlow/PyTorch, XGBoost, etc.). Experience in NLP related to Semantic models/Search using BERT/ transformer model. Experience with Gen AI ecosystem/tools is a plus. Experience in data wrangling using Pandas/Polaris, NumPy, SQL, etc. Good grasp of software engineering principles (version control, testing, modular code). Preferred Technical And Professional Experience Familiarity with REST APIs and deployment practices (Dockerized Container, Flask/FastAPI, etc.). Understanding of cloud platforms (AWS, GCP, Azure) is a plus. Problem-Solving: Excellent analytical and problem-solving skills, with the ability to think critically and creatively. Communication: Strong interpersonal and communication skills, with the ability to work effectively in a collaborative team environment

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Data Scientist AI Garage is responsible for establishing Mastercard as an AI powerhouse. AI will be leveraged and implemented at scale within Mastercard providing a foundational, competitive advantage for the future. All internal processes, all products and services will be enabled by AI continuously advancing our value proposition, consumer experience, and efficiency. Opportunity Join Mastercard's AI Garage @ Gurgaon, a newly created strategic business unit executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI. The AI professional will be responsible for the creative application and execution of AI use cases, working collaboratively with other AI professionals and business stakeholders to effectively drive the AI mandate. Role Ensure all AI solution development is in line with industry standards for data management and privacy compliance including the collection, use, storage, access, retention, output, reporting, and quality of data at Mastercard Adopt a pragmatic approach to AI, capable of articulating complex technical requirements in a manner this is simple and relevant to stakeholder use cases Gather relevant information to define the business problem interfacing with global stakeholders Creative thinker capable of linking AI methodologies to identified business challenges Identify commonalities amongst use cases enabling a microservice approach to scaling AI at Mastercard, building reusable, multi-purpose models Develop AI/ML solutions/applications leveraging the latest industry and academic advancements Leverage open and closed source technologies to solve business problems Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda Partner with technical teams to implement developed solutions/applications in production environment Support a learning culture continuously advancing AI capabilities All About You Experience Experience in the Data Sciences field with a focus on AI strategy and execution and developing solutions from scratch Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: o Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL o Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning o Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil o Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing o Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Exposure or experience using collaboration tools such as: o Confluence (Documentation) o Bitbucket/Stash (Code Sharing) o Shared Folders (File Sharing) o ALM (Project Management) Knowledge of payments industry a plus Experience with SAFe (Scaled Agile Framework) process is a plus Effectiveness Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum Capable of navigating a complex organization in a relentless pursuit of answers and clarity Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organization's effectiveness Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment Incredible attention to detail and focus instilling confidence without qualification in developed solutions Core Capabilities Strong written and oral communication skills Strong project management skills Concentration in Computer Science Some international travel required Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Manager Data Scientist AI Garage is responsible for establishing Mastercard as an AI powerhouse. AI will be leveraged and implemented at scale within Mastercard providing a foundational, competitive advantage for the future. All internal processes, all products and services will be enabled by AI continuously advancing our value proposition, consumer experience, and efficiency. Opportunity Join Mastercard's AI Garage @ Gurgaon, a newly created strategic business unit executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI. The AI professional will be responsible for the creative application and execution of AI use cases, working collaboratively with other AI professionals and business stakeholders to effectively drive the AI mandate. Role Ensure all AI solution development is in line with industry standards for data management and privacy compliance including the collection, use, storage, access, retention, output, reporting, and quality of data at Mastercard Adopt a pragmatic approach to AI, capable of articulating complex technical requirements in a manner this is simple and relevant to stakeholder use cases Gather relevant information to define the business problem interfacing with global stakeholders Creative thinker capable of linking AI methodologies to identified business challenges Identify commonalities amongst use cases enabling a microservice approach to scaling AI at Mastercard, building reusable, multi-purpose models Develop AI/ML solutions/applications leveraging the latest industry and academic advancements Leverage open and closed source technologies to solve business problems Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda Partner with technical teams to implement developed solutions/applications in production environment Support a learning culture continuously advancing AI capabilities All About You Experience Experience in the Data Sciences field with a focus on AI strategy and execution and developing solutions from scratch Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: o Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL o Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning o Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil o Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing o Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Exposure or experience using collaboration tools such as: o Confluence (Documentation) o Bitbucket/Stash (Code Sharing) o Shared Folders (File Sharing) o ALM (Project Management) Knowledge of payments industry a plus Experience with SAFe (Scaled Agile Framework) process is a plus Effectiveness Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum Capable of navigating a complex organization in a relentless pursuit of answers and clarity Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organization's effectiveness Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment Incredible attention to detail and focus instilling confidence without qualification in developed solutions Core Capabilities Strong written and oral communication skills Strong project management skills Concentration in Computer Science Some international travel required #AI1 Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

For 3–5 Years Experience Please share your updated via anjali.sharma@genicminds.com _ AI/ML Engineer / Data Scientist _ 1. Core Technical Skills Python (NumPy, Pandas, Scikit-learn, Matplotlib/Seaborn, beautifulsoup, selenium) SQL(MySQL/PostgreSQL), Mongo DB, NLP, Computer Vision, RAG, Vector DBs, LLMs, Agentic AI, Neural Network, RNN, CNN, LSTMs, web scraping. ML algorithms: regression, decision trees, random forests, XGBoost, SVM, KMeans, DBSCAN, etc. Model evaluation: cross-validation, precision/recall, ROC-AUC, confusion matrix 2. AI/ML Frameworks Scikit-learn, TensorFlow or PyTorch Keras Familiar with pre-trained models (e.g., BERT, ResNet, Stable Diffusion) and transfer learning 3. Practical Experience Building and deploying end-to-end ML pipeline Experience with REST APIs or Flask/FastAPI-based model deployment Version control with Git 4. Data Handling Data preprocessing, feature engineering Experience with structured, semi-structured data and unstructured data Data visualization (Power BI, Tableau, or Python libs) 5. Cloud & DevOps Basics Working knowledge of AWS/GCP/Azure (S3, Lambda, SageMaker or equivalent) Docker CI/CD understanding 6. Soft Skills Good documentation practices Able to explain ML models to non-tech stakeholders Cross-functional collaboration experience Job Types: Full-time, Permanent Schedule: Day shift Work Location: In person

For 3–5 Years Experience – Mid-Level AI/ML Engineer / Data Scientist 1. Core Technical Skills Python (NumPy, Pandas, Scikit-learn, Matplotlib/Seaborn, beautifulsoup, selenium) SQL(MySQL/PostgreSQL), Mongo DB, NLP, Computer Vision, RAG, Vector DBs, LLMs, Agentic AI, Neural Network, RNN, CNN, LSTMs, web scraping. ML algorithms: regression, decision trees, random forests, XGBoost, SVM, KMeans, DBSCAN, etc. Model evaluation: cross-validation, precision/recall, ROC-AUC, confusion matrix 2. AI/ML Frameworks Scikit-learn, TensorFlow or PyTorch Keras Familiar with pre-trained models (e.g., BERT, ResNet, Stable Diffusion) and transfer learning 3. Practical Experience Building and deploying end-to-end ML pipelines Experience with REST APIs or Flask/FastAPI-based model deployment Version control with Git 4. Data Handling Data preprocessing, feature engineering Experience with structured, semi-structured data and unstructured data Data visualization (Power BI, Tableau, or Python libs) 5. Cloud & DevOps Basics Working knowledge of AWS/GCP/Azure (S3, Lambda, SageMaker or equivalent) Docker CI/CD understanding 6. Soft Skills Good documentation practices Able to explain ML models to non-tech stakeholders Cross-functional collaboration experience Job Types: Full-time, Permanent Pay: ₹450,000.00 - ₹650,000.00 per year Work Location: In person

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Analyst, Inclusive Innovation & Analytics, Center for Inclusive Growth Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. The Center for Inclusive Growth is the social impact hub at Mastercard. The organization seeks to ensure that the benefits of an expanding economy accrue to all segments of society. Through actionable research, impact data science, programmatic grants, stakeholder engagement and global partnerships, the Center advances equitable and sustainable economic growth and financial inclusion around the world. The Center’s work is at the heart of Mastercard’s objective to be a force for good in the world. Reporting to Vice President, Inclusive Innovation & Analytics, the Analyst, will 1) create and/or scale data, data science, and AI solutions, methodologies, products, and tools to advance inclusive growth and the field of impact data science, 2) work on the execution and implementation of key priorities to advance external and internal data for social strategies, and 3) manage the operations to ensure operational excellence across the Inclusive Innovation & Analytics team. Key Responsibilities Data Analysis & Insight Generation Design, develop, and scale data science and AI solutions, tools, and methodologies to support inclusive growth and impact data science. Analyze structured and unstructured datasets to uncover trends, patterns, and actionable insights related to economic inclusion, public policy, and social equity. Translate analytical findings into insights through compelling visualizations and dashboards that inform policy, program design, and strategic decision-making. Create dashboards, reports, and visualizations that communicate findings to both technical and non-technical audiences. Provide data-driven support for convenings involving philanthropy, government, private sector, and civil society partners. Data Integration & Operationalization Assist in building and maintaining data pipelines for ingesting and processing diverse data sources (e.g., open data, text, survey data). Ensure data quality, consistency, and compliance with privacy and ethical standards. Collaborate with data engineers and AI developers to support backend infrastructure and model deployment. Team Operations Manage team operations, meeting agendas, project management, and strategic follow-ups to ensure alignment with organizational goals. Lead internal reporting processes, including the preparation of dashboards, performance metrics, and impact reports. Support team budgeting, financial tracking, and process optimization. Support grantees and grants management as needed Develop briefs, talking points, and presentation materials for leadership and external engagements. Translate strategic objectives into actionable data initiatives and track progress against milestones. Coordinate key activities and priorities in the portfolio, working across teams at the Center and the business as applicable to facilitate collaboration and information sharing Support the revamp of the Measurement, Evaluation, and Learning frameworks and workstreams at the Center Provide administrative support as needed Manage ad-hoc projects, events organization Qualifications Bachelor’s degree in Data Science, Statistics, Computer Science, Public Policy, or a related field. 2–4 years of experience in data analysis, preferably in a mission-driven or interdisciplinary setting. Strong proficiency in Python and SQL; experience with data visualization tools (e.g., Tableau, Power BI, Looker, Plotly, Seaborn, D3.js). Familiarity with unstructured data processing and robust machine learning concepts. Excellent communication skills and ability to work across technical and non-technical teams. Technical Skills & Tools Data Wrangling & Processing Data cleaning, transformation, and normalization techniques Pandas, NumPy, Dask, Polars Regular expressions, JSON/XML parsing, web scraping (e.g., BeautifulSoup, Scrapy) Machine Learning & Modeling Scikit-learn, XGBoost, LightGBM Proficiency in supervised/unsupervised learning, clustering, classification, regression Familiarity with LLM workflows and tools like Hugging Face Transformers, LangChain (a plus) Visualization & Reporting Power BI, Tableau, Looker Python libraries: Matplotlib, Seaborn, Plotly, Altair Dashboarding tools: Streamlit, Dash Storytelling with data and stakeholder-ready reporting Cloud & Collaboration Tools Google Cloud Platform (BigQuery, Vertex AI), Microsoft Azure Git/GitHub, Jupyter Notebooks, VS Code Experience with APIs and data integration tools (e.g., Airflow, dbt) Ideal Candidate You are a curious and collaborative analyst who believes in the power of data to drive social change. You’re excited to work with cutting-edge tools while staying grounded in the real-world needs of communities and stakeholders. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Software Engineer II We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You : Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Manager Data Scientist AI Garage is responsible for establishing Mastercard as an AI powerhouse. AI will be leveraged and implemented at scale within Mastercard providing a foundational, competitive advantage for the future. All internal processes, all products and services will be enabled by AI continuously advancing our value proposition, consumer experience, and efficiency. Opportunity Join Mastercard's AI Garage @ Gurgaon, a newly created strategic business unit executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI. The AI professional will be responsible for the creative application and execution of AI use cases, working collaboratively with other AI professionals and business stakeholders to effectively drive the AI mandate. Role Ensure all AI solution development is in line with industry standards for data management and privacy compliance including the collection, use, storage, access, retention, output, reporting, and quality of data at Mastercard Adopt a pragmatic approach to AI, capable of articulating complex technical requirements in a manner this is simple and relevant to stakeholder use cases Gather relevant information to define the business problem interfacing with global stakeholders Creative thinker capable of linking AI methodologies to identified business challenges Identify commonalities amongst use cases enabling a microservice approach to scaling AI at Mastercard, building reusable, multi-purpose models Develop AI/ML solutions/applications leveraging the latest industry and academic advancements Leverage open and closed source technologies to solve business problems Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda Partner with technical teams to implement developed solutions/applications in production environment Support a learning culture continuously advancing AI capabilities Experience All About You Experience in the Data Sciences field with a focus on AI strategy and execution and developing solutions from scratch Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Exposure or experience using collaboration tools such as: Confluence (Documentation) Bitbucket/Stash (Code Sharing) Shared Folders (File Sharing) ALM (Project Management) Knowledge of payments industry a plus Experience with SAFe (Scaled Agile Framework) process is a plus Effectiveness Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum Capable of navigating a complex organization in a relentless pursuit of answers and clarity Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organization's effectiveness Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment Incredible attention to detail and focus instilling confidence without qualification in developed solutions Core Capabilities Strong written and oral communication skills Strong project management skills Concentration in Computer Science Some international travel required #AI1 Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.