397 Svm Jobs - Page 5

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. Primary Skills – Python, AI, ML (Machine Learning) Gen AI – Generative AI + RAG, NLP, LLM, Deep Learning, Computer Vision, AWS, Cloud Or Azure Open AI (Any Cloud) Experience- 5+ to 12 Years Job Location- Kolkata Responsibilities More than 5 years of experience in Data Science and AI / ML domain Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience using business intelligence tools (e.g., Tableau, PowerBI) and data frameworks (e.g., Hadoop) Experience in Cloud native skills. Knowledge of SQL and Python; familiarity with Scala. Analytical mind and business acumen and Strong math skills (e.g., statistics, algebra) Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable. Experience with NLP, NLG, and Large Language Models like – BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc. Great communication and presentation skills. Should have experience in working in a fast-paced team culture. Experience with AI/ML like – AWS Sage Maker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc. Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databases. Good understanding of applied statistics skills, such as distributions, statistical testing, regression, etc. Should be a data-oriented person with analytical mind and business acumen.

Summary: We are seeking a talented and motivated AI Engineer to join our team and focus on building cutting-edge Generative AI applications. The ideal candidate will possess a strong background in data science, machine learning, and deep learning, with specific experience in developing and fine-tuning Large Language Models (LLMs) and Small Language Models (SLMs). You should be comfortable managing the full lifecycle of AI projects, from initial design and data handling to deployment and production monitoring. A foundational understanding of software engineering principles is also required to collaborate effectively with engineering teams and ensure robust deployments. Responsibilities: Design, develop, and implement Generative AI solutions, including applications leveraging Retrieval-Augmented Generation (RAG) techniques. Fine-tune existing Large Language Models (LLMs) and potentially develop smaller, specialized language models (SLMs) for specific tasks. Manage the end-to-end lifecycle of AI model development, including data curation, feature extraction, model training, validation, deployment, and monitoring. Research and experiment with state-of-the-art AI/ML/DL techniques to enhance model performance and capabilities. Build and maintain scalable production pipelines for AI models. Collaborate with data engineering and IT teams to define deployment roadmaps and integrate AI solutions into existing systems. Develop AI-powered tools to solve business problems, such as summarization, chatbots, recommendation systems, or code assistance. Stay updated with the latest advancements in Generative AI, machine learning, and deep learning. Qualifications: Proven experience as a Data Scientist, Machine Learning Engineer, or AI Engineer with a focus on LLMs and Generative AI. Strong experience with Generative AI techniques and frameworks (e.g., RAG, Fine-tuning, Langchain, LlamaIndex, PEFT, LoRA). Solid foundation in machine learning (e.g., Regression, Classification, Clustering, XGBoost, SVM) and deep learning (e.g., ANN, LSTM, RNN, CNN) concepts and applications. Proficiency in Python and relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch). Experience with data science principles, including statistics, hypothesis testing, and A/B testing. Experience deploying and managing models in production environments (e.g., using platforms like AWS, Databricks, MLFlow). Familiarity with data handling and processing tools (e.g., SQL, Spark/PySpark). Basic understanding of software engineering practices, including version control (Git) and containerization (Docker). Bachelor's or master’s degree in computer science, Artificial Intelligence, Data Science, or a related quantitative field. Preferred Skills: Experience building RAG-based chatbots or similar applications. Experience developing custom SLMs. Experience with MLOps principles and tools (e.g., MLFlow, Airflow). Experience migrating ML workflows between cloud platforms. Familiarity with vector databases and indexing techniques. Experience with Python web frameworks (e.g., Django, Flask). Experience building and integrating APIs (e.g., RESTful APIs). Basic experience with front-end development or UI building for showcasing AI applications. Qualifications Bachelorʼs or Masterʼs degree in Computer Science, Engineering, or a related discipline.

Description We are looking for a Strategic account manager responsible for the growth and development of some of the most influential sellers on the Amazon.in marketplace. The ideal candidate thrives in an ambiguous environment where they must develop, implement and iterate on business strategies to deliver growth and positive experience for sellers. The candidate should be hands-on, detail oriented, have relentlessly high standards and operates as a business owner who understands key levers to achieve results through their team. In this role, the candidate will be responsible for achieving the top line nos. for the business by driving strategic business and operational objectives. The candidate will drive the creation and execution of strategies to achieve business goals through his team by focusing on selection expansion, leveraging Fulfillment channels for faster delivery, developing merchandising strategy and improving catalog quality. The candidate will use his category expertise to drive seller interactions & act as a Voice of Seller influencing Marketplace policies on Seller Fees and Policies, in areas like Reimbursements, Returns, Seller Claims etc. The candidate would need to actively collaborate with other stakeholders like Category Management, Fulfillment, Finance, Product & Advertising teams to align programs and initiatives to identify potential growth avenues and drive seller success. If you are interested in growing brands and businesses on Amazon, we’re interested in talking to you! Key job responsibilities Business Growth Contribute to business strategy development and identify correct input metrics that drive growth and improve the end customer & seller experience, in collaboration with cross-functional teams and other Amazon programs. Possess the ability to manage and deliver against complex goals where strategy is not defined. Able to make tradeoffs between short term seller needs and longer-term strategic investment. Relationship Management Build and cultivate strong relationships with sellers in your portfolio along with internal stakeholders; be a trusted advisor and a business advocate. Process Excellence Use customer feedback, market growth trends, and analyze key metrics to contribute to strategic development of features and programs that accelerate seller’s growth and improve their experience working with Amazon. Spot areas of unnecessary process or inefficiencies and work to simplify. Identify, optimize, and scale improvements that can benefit a large set of customers, e.g. driving efficiencies through tools and processes, simplifying SOPs, etc., working across multiple organizations. Develop mechanisms to create accountability. Basic Qualifications 2+ years of sales experience Experience analyzing data and best practices to assess performance drivers Preferred Qualifications Experience in e-commerce - Experience meeting revenue targets and quotas - Experience in e-commerce - Experience working in a fast-paced and highly cross-functional organization Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ASSPL - Haryana - C77 Job ID: A3035069

Coditas Solutions is seeking a highly skilled and motivated Lead Data Scientist to join our dynamic team. As a Data Scientist, you will play a key role in designing, implementing, and optimizing machine learning models and algorithms to solve complex business challenges. If you have a passion for leveraging AI and ML technologies to drive innovation, this is an exciting opportunity to contribute to groundbreaking projects. Roles and Responsibilities ● Lead the design, implementation, and optimization of machine learning and AI models using Python and R. ● Develop and deploy scalable predictive models and decision-making systems for business-critical applications. ● Conduct advanced exploratory data analysis (EDA) to extract actionable insights from structured and unstructured data. ● Collaborate with data engineers to ensure high-quality, well-structured datasets for training and inference. ● Own the end-to-end model lifecycle, from development to deployment, monitoring, and continuous improvement. ● Guide the integration of AI/ML models into enterprise-level production systems in collaboration with software engineering teams. ● Provide technical leadership, mentoring junior data scientists and driving best practices in ML model development and deployment. ● Stay ahead of the curve by evaluating and implementing cutting-edge AI/ML advancements, including LLMs and GenAI models. ● Work closely with stakeholders, product teams, and clients to define business challenges and design AI-driven solutions. ● Drive model interpretability, explainability, and responsible AI practices within the organization. Technical Skills ● 6-14 years of hands-on experience in designing and implementing machine learning, deep learning, and AI solutions . ● Strong programming expertise in Python and R , with proficiency in implementing complex algorithms. ● Extensive experience with cloud platforms (AWS, Azure, GCP) for deploying scalable machine learning solutions. ● Proficiency in MLOps practices , ensuring robust model deployment, monitoring, and retraining workflows. ● Strong background in classical ML algorithms (e.g., linear regression, logistic regression, decision trees, random forests, SVM) and deep learning architectures (CNNs, RNNs, Transformers). ● Hands-on experience with ML/DL libraries such as Scikit-learn, TensorFlow, PyTorch, Keras, NLTK, OpenCV . ● Expertise in data preprocessing, feature engineering, and model evaluation for structured and unstructured data. ● Proven experience in selecting and engineering relevant features to enhance model performance. ● Understanding of LLMs (Large Language Models) and GenAI technologies , with the ability to optimize their usage for enterprise applications. ● Strong problem-solving, critical thinking, and analytical skills to drive AI/ML innovations. ● Exceptional communication and leadership skills , with experience in mentoring teams and collaborating with cross-functional stakeholders.

Requisition ID 167665 - Posted 07/16/2025 - Analytics - India - Maharashtra - Mumbai - Colgate-Palmolive - No Travel - Remote Relocation Assistance Offered Within Country Job Number #167665 - Mumbai, Maharashtra, India Who We Are Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name! Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all. Title: Senior Specialist, Global Data Science Brief introduction - Role Summary/Purpose: The GLOBAL DATA SCIENCE & ADVANCED ANALYTICS vertical in Colgate Palmolive is focused on working on business cases which have a big $ impact for the business addressing the business questions, with recommended actions and scope for scalability across markets. The Data Scientist position would lead GLOBAL DATA SCIENCE & ADVANCED ANALYTICS projects within the Analytics Continuum. The position conceptualizes and builds machine learning, predictive modeling , simulations, and optimization solutions for clear dollar objectives and measured value for Colgate Palmolive The role would require, to work on a range of GLOBAL DATA SCIENCE & ADVANCED ANALYTICS projects across Revenue Growth Management, Price Elasticity, Promotion Analytics, Marketing Mix Modeling Data Scientist needs to manage relationships independently with Business and stakeholders to drive projects Responsibilities : Conceptualizes and builds predictive modeling, simulations, and optimization solutions to address business questions or use cases Applies ML and AI to analytics algorithms to build inferential and predictive models allowing for scalable solutions to be deployed across the business Develops end to end business solutions from data extraction, data preparation, data mining to statistical modeling and then building business presentations Conducts model validations and continuous improvement of the algorithms, capabilities, or solutions built Deploys models using Airflow, Docker on Google Cloud Platforms Own Pricing and Promotion, Marketing Mix from scoping to delivery Study large amounts of data to discover trends and patterns Mine data through various technologies like BigQuery and SQL Present insights in an easy to interpret way to the business teams Develop visualization (e.g. Looker, PyDash, Flask, PlotLy, streamlit) using large datasets and model output datasets Ready to work closely with business partners across geographies Required Qualifications : BE/BTECH [ Computer Science, Information Technology is preferred ], MBA or PGDM in Business Analytics / Data Science, Additional DS Certifications or Courses, MSC / MSTAT in Economics or Statistics 5+ years of experience in building statistical models and driving insights Hands-on/experience on developing statistical models, such as linear regression, ridge regression, lasso, random forest, SVM, gradient boosting, logistic regression, K-Means Clustering, Hierarchical Clustering, Bayesian Regression etc. Hands on experience on coding languages Python(mandatory) and SQL Knowledge of using GitHub, Airflow for coding and model deployments Understand visualization frameworks PyDash, Flask, PlotLy Strong Understanding of Cloud Frameworks Google Cloud, Snowflake and services like Kubernetes, Cloud Build Cloud Run. Experience front facing Business teams (Client facing role) supporting and working with multi-functional teams in a dynamic environment Preferred Qualifications : Managing, transforming, and developing statistical models for RGM/Pricing and/or Marketing Mix Models Experience with third-party data i.e., syndicated market data, Point of Sales, etc. Working knowledge of consumer packaged goods industry Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Knowledge of Google Cloud products (BigQuery, data studio, kubernetes, cloud build, cloud run etc) Knowledge of deployment of models in Cloud Environment using Airflow, Docker Our Commitment to Inclusion Our journey begins with our people—developing strong talent with diverse backgrounds and perspectives to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business. Equal Opportunity Employer Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law. Reasonable accommodation during the application process is available for persons with disabilities. Please complete this request form should you require accommodation. #LI-Remote

Location Gurugram, Haryana, India This job is associated with 2 categories Job Id GGN00002106 Information Technology Job Type Full-Time Posted Date 07/16/2025 Achieving our goals starts with supporting yours. Grow your career, access top-tier health and wellness benefits, build lasting connections with your team and our customers, and travel the world using our extensive route network. Come join us to create what’s next. Let’s define tomorrow, together. Description United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions. Job overview and responsibilities United Airlines’ Enterprise Data Analytics department partners with business and technology leaders across the company to transform data analytics into a competitive advantage. An offshore team based in Delhi, India will work closely with this group and support it with complementing skills and capabilities. The key objectives are to improve operating performance, boost customer experience and drive incremental revenue by embedding data in decision making across all levels of the organization. An entry level data analyst will be responsible for data, analytics and modeling to dig deep into details as well as to assess the big picture. Execute solutions to business problems using data analysis, data mining, optimization tools, statistical modeling and machine learning techniques Continuously develop and improved analysis methodologies Analyze and model data and working from concept through to execution Understand a business problem and the available data and identify what analytics and modeling techniques can be applied to answer a business question This position is offered on local terms and conditions. Expatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded. This position is for United Airlines Business Services Pvt. Ltd - a wholly owned subsidiary of United Airlines Inc. Qualifications What’s needed to succeed (Minimum Qualifications): Bachelor's degree Quantitative field like Math, Statistics, Operations Research At least 2+ years of experience in modeling/ machine learning required Proven comfort and an intellectual curiosity for working with very large sets of data, and hands-on knowledge in predictive modeling Strong knowledge of either R or Python Be experienced in manipulating and analyzing complex, high-volume, high dimensionality data from various sources to highlight patterns and relationships Understanding of how and when to apply predictive and machine learning techniques like logistic regression, random forest, GBM, Neural Nets, SVM etc. is required Be proficient in using database querying tools and able to write complex queries and procedures using Teradata SQL and/or Microsoft TSQL Hands on experience in using Big Data ecosystems (Hadoop/Spark), API Gateways and non-structured data will be a plus Being able to communicate complex quantitative analysis and algorithms in a clear, precise and actionable manner Must be legally authorized to work in India for any employer without sponsorship Must be fluent in English (written and spoken) Successful completion of interview required to meet job qualification Reliable, punctual attendance is an essential function of the position What will help you propel from the pack (Preferred Qualifications): Master's degree

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems. The Opportunity When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills. As part of the Data Science team you will design and deliver scalable AI applications that drive business transformation. As a Senior Associate you will analyze complex problems, mentor junior team members, and build meaningful client connections while navigating the evolving landscape of AI and machine learning. This role offers the chance to work on innovative technologies, collaborate with cross-functional teams, and contribute to creative solutions that shape the future of the industry. Responsibilities Design and implement scalable AI applications to facilitate business transformation Analyze intricate problems and propose practical solutions Mentor junior team members to enhance their skills and knowledge Establish and nurture meaningful relationships with clients Navigate the dynamic landscape of AI and machine learning Collaborate with cross-functional teams to drive innovative solutions Utilize advanced technologies to improve project outcomes Contribute to the overall strategy of the Data Science team What You Must Have Bachelor's Degree in Computer Science, Engineering, or equivalent technical discipline 4-9 years of experience in Data Science/ML/AI roles Oral and written proficiency in English required What Sets You Apart Proficiency in Python and data science libraries Hands-on experience with Generative AI and prompt engineering Familiarity with cloud platforms like Azure, AWS, GCP Understanding of production-level AI systems and CI/CD Experience with Docker, Kubernetes for ML workloads Knowledge of MLOps tooling and pipelines Demonstrated track record of delivering AI-driven solutions Preferred Knowledge/Skills Please reference About PwC CTIO – AI Engineering PwC’s Commercial Technology and Innovation Office (CTIO) is at the forefront of emerging technology, focused on building transformative AI-powered products and driving enterprise innovation. The AI Engineering team within CTIO is dedicated to researching, developing, and operationalizing cutting-edge technologies such as Generative AI, Large Language Models (LLMs), AI Agents, and more. Our mission is to continuously explore what's next—enabling business transformation through scalable AI/ML solutions while remaining grounded in research, experimentation, and engineering excellence.ill categories for job description details. Role Overview We are seeking a Senior Associate – Data Science/ML/DL/GenAI to join our high-impact, entrepreneurial team. This individual will play a key role in designing and delivering scalable AI applications, conducting applied research in GenAI and deep learning, and contributing to the team’s innovation agenda. This is a hands-on, technical role ideal for professionals passionate about AI-driven transformation. Key Responsibilities Design, develop, and deploy machine learning, deep learning, and Generative AI solutions tailored to business use cases. Build scalable pipelines using Python (and frameworks such as Flask/FastAPI) to operationalize data science models in production environments. Prototype and implement solutions using state-of-the-art LLM frameworks such as LangChain, LlamaIndex, LangGraph, or similar. Also developing applications in streamlit/chainlit for demo purposes. Design advanced prompts and develop agentic LLM applications that autonomously interact with tools and APIs. Fine-tune and pre-train LLMs (HuggingFace and similar libraries) to align with business objectives. Collaborate in a cross-functional setup with ML engineers, architects, and product teams to co-develop AI solutions. Conduct R&D in NLP, CV, and multi-modal tasks, and evaluate model performance with production-grade metrics. Stay current with AI research and industry trends; continuously upskill to integrate the latest tools and methods into the team’s work. Required Skills & Experience 4 to 9 years of experience in Data Science/ML/AI roles. Bachelor’s degree in Computer Science, Engineering, or equivalent technical discipline (BE/BTech/MCA). Proficiency in Python and related data science libraries: Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Keras, etc. Hands-on experience with Generative AI, including prompt engineering, LLM fine-tuning, and deployment. Experience with Agentic LLMs and task orchestration using tools like LangGraph or AutoGPT-like flows. Strong knowledge of NLP techniques, transformer architectures, and text analysis. Proven experience working with cloud platforms (preferably Azure; AWS/GCP also considered). Understanding of production-level AI systems including CI/CD, model monitoring, and cloud-native architecture. (Need not develop from scratch) Familiarity with ML algorithms: XGBoost, GBM, k-NN, SVM, Decision Forests, Naive Bayes, Neural Networks, etc. Exposure to deploying AI models via APIs and integration into larger data ecosystems. Strong understanding of model operationalization and lifecycle management. Experience with Docker, Kubernetes, and containerized deployments for ML workloads. Use of MLOps tooling and pipelines (e.g., MLflow, Azure ML, SageMaker, etc.). Experience in full-stack AI applications, including visualization (e.g., PowerBI, D3.js). Demonstrated track record of delivering AI-driven solutions as part of large-scale systems.

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of yourself. Your unique voice and perspective are valued to help EY become even better. Join us and contribute to building an exceptional experience for yourself and creating a better working world for all. As a part of our EY - Technology Risk team, you will contribute technically to IT Risk and Assurance client engagements as well as internal projects. Your role will involve actively establishing, maintaining, and strengthening internal and external relationships. You will also be responsible for identifying potential business opportunities for Ernst & Young within existing engagements and escalating them as appropriate. Anticipating and identifying risks within engagements and sharing any issues with senior team members will also be part of your responsibilities. The opportunity entails helping clients navigate the complex world of modern data science and analytics. You will provide advice to clients on designing, implementing, stabilizing, and optimizing internal controls using cutting-edge and scalable AI & Big Data technologies. Your key responsibilities include: - Building and leveraging cutting-edge Gen AI & Big Data platforms to deliver insights for comprehensive Risk & Controls monitoring mechanisms. - Creating executive reporting, proposals, and marketing material with the highest quality deliverables. - Collaborating within the team to solve technical challenges in the design and development of the next-generation AI & Data-led Risk technology platform. To qualify for this role, you must have: - 4+ years of working experience in Large Scale AI/ML models and data science. - Deep understanding of statistics, AI/ML algorithms, and predictive modeling. - Proficiency in AI/ML programming languages like Python, R, and SQL. - Expertise in machine learning algorithms and data mining techniques including deep learning algorithms. - Strong programming skills in Python with machine learning libraries such as Scikit-learn, Pandas, NumPy, etc. - Knowledge of tools such as Docker, Kubernetes, Git, and deep learning frameworks like TensorFlow, PyTorch, or Keras. Ideally, you'll also have a Bachelor's Degree or above in mathematics, information systems, statistics, computer science, Data Science, or related disciplines. Relevant certifications are considered a plus. Being self-driven, a creative problem solver, and enjoying the fast-paced environment of software development are qualities that are valued. At EY, you will have opportunities to work with leading businesses globally and develop your skills and career. You will work on inspiring and meaningful projects, receive support, coaching, and feedback from engaging colleagues, and have the freedom and flexibility to handle your role in a way that suits you. EY is committed to building a better working world by creating long-term value for clients, people, and society through trust, data, and technology.,

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. R-251749

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. R-251749

Summary: We are seeking a talented and motivated AI Engineer to join our team and focus on building cutting-edge Generative AI applications. The ideal candidate will possess a strong background in data science, machine learning, and deep learning, with specific experience in developing and fine-tuning Large Language Models (LLMs) and Small Language Models (SLMs). You should be comfortable managing the full lifecycle of AI projects, from initial design and data handling to deployment and production monitoring. A foundational understanding of software engineering principles is also required to collaborate effectively with engineering teams and ensure robust deployments. Responsibilities: Design, develop, and implement Generative AI solutions, including applications leveraging Retrieval-Augmented Generation (RAG) techniques. Fine-tune existing Large Language Models (LLMs) and potentially develop smaller, specialized language models (SLMs) for specific tasks. Manage the end-to-end lifecycle of AI model development, including data curation, feature extraction, model training, validation, deployment, and monitoring. Research and experiment with state-of-the-art AI/ML/DL techniques to enhance model performance and capabilities. Build and maintain scalable production pipelines for AI models. Collaborate with data engineering and IT teams to define deployment roadmaps and integrate AI solutions into existing systems. Develop AI-powered tools to solve business problems, such as summarization, chatbots, recommendation systems, or code assistance. Stay updated with the latest advancements in Generative AI, machine learning, and deep learning. Qualifications: Proven experience as a Data Scientist, Machine Learning Engineer, or AI Engineer with a focus on LLMs and Generative AI. Strong experience with Generative AI techniques and frameworks (e.g., RAG, Fine-tuning, Langchain, LlamaIndex, PEFT, LoRA). Solid foundation in machine learning (e.g., Regression, Classification, Clustering, XGBoost, SVM) and deep learning (e.g., ANN, LSTM, RNN, CNN) concepts and applications. Proficiency in Python and relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch). Experience with data science principles, including statistics, hypothesis testing, and A/B testing. Experience deploying and managing models in production environments (e.g., using platforms like AWS, Databricks, MLFlow). Familiarity with data handling and processing tools (e.g., SQL, Spark/PySpark). Basic understanding of software engineering practices, including version control (Git) and containerization (Docker). Bachelor's or master’s degree in computer science, Artificial Intelligence, Data Science, or a related quantitative field. Preferred Skills: Experience building RAG-based chatbots or similar applications. Experience developing custom SLMs. Experience with MLOps principles and tools (e.g., MLFlow, Airflow). Experience migrating ML workflows between cloud platforms. Familiarity with vector databases and indexing techniques. Experience with Python web frameworks (e.g., Django, Flask). Experience building and integrating APIs (e.g., RESTful APIs). Basic experience with front-end development or UI building for showcasing AI applications. Qualifications Bachelorʼs or Masterʼs degree in Computer Science, Engineering, or a related discipline.

We’re seeking an experienced AI/ML Lead to design, develop, and deploy advanced machine learning and AI solutions, including deep learning, computer vision, NLP, and generative AI. You'll work on scalable, cloud-native systems and lead the end-to-end development lifecycle. Key Responsibilities: Build and deploy ML models (Deep Learning, RL, CV, NLP, GenAI). Design ML architectures for native/hybrid cloud (AWS, Azure, GCP). Develop scalable ML services, pipelines, and APIs. Create demos, PoCs, and AI-driven products. Write functional and technical specs for ML solutions. Apply DevOps/MLOps practices (CI/CD, monitoring). Collaborate with cross-functional teams for innovative AI solutions. Required Skills: Strong Python (R/Scala optional), SQL & NoSQL Expertise in TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas Experience with ML algorithms: CNN, RNN, SVM, Random Forest, Q-Learning, etc. Hands-on with SDLC, data pipelines, and model deployment at scale Familiarity with frameworks like MxNet, TensorFlow, and modern ML tools Preferred: MLOps/DevOps experience (CI/CD) Cloud ML experience (AWS, Azure, GCP) Exposure to generative AI, transfer learning, and expert systems Qualifications: B.Tech / M.Tech / Ph.D. in CS, IT, AI, or related fields MSc (Statistics) or MCA also considered Job Type: Full-time Pay: From ₹1,000,000.00 per year Benefits: Provident Fund Work Location: In person

Job Description: As a Machine Learning Engineer at Agnisys, you will play a crucial role in designing, developing, and deploying machine learning models, particularly in the field of Natural Language Processing (NLP). The ideal candidate should have a strong foundation in mathematical concepts of ML algorithms and hands-on experience with transformer architectures. Responsibilities: 1. **Mathematical Proficiency:** - Demonstrate a solid understanding of mathematical concepts underlying machine learning algorithms. - Apply mathematical principles to design and optimize machine learning models. - Good understanding of Supervised Learning algorithms like Logistic Regression, Linear Regression, SVM, Decision Trees, Ensemble Techniques (Bagging, Boosting), etc. - Experience with Unsupervised Learning algorithms, such as clustering (k-means, hierarchical clustering).2. **NLP Expertise:** - Possess practical experience in working with NLP technologies. - Showcase a deep understanding of transformer architecture and its applications in NLP tasks.3. **Advanced Concepts:** - Familiarity with advanced concepts such as prompt engineering, retrieval augmented generation, and reinforcement learning is highly desirable. - Proactively stay updated on the latest advancements in ML, including Deep Neural Networks (MLP, CNN, LSTM, GRUs), and incorporate relevant techniques into projects.4. **Deployment Experience:** - Have a proven track record of deploying machine learning models into production environments. - Ensure scalability, reliability, and maintainability of deployed ML systems. Qualifications: - Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, or a related field. - Solid understanding of machine learning algorithms, statistical modeling, and supervised/unsupervised learning techniques. - Hands-on experience with NLP technologies, with a focus on transformer architectures. - Familiarity with prompt engineering, retrieval augmented generation, and reinforcement learning is a plus. - Proven experience in deploying machine learning models in production. - Strong programming skills in languages such as Python, TensorFlow, and PyTorch. - Excellent problem-solving and communication skills. Job Type: Full-time Pay: ₹360,020.77 - ₹1,595,226.79 per year Benefits: Health insurance Work from home Schedule: Day shift Supplemental Pay: Yearly bonus Work Location: In person

About the Company RADcube – A Stlogics Company is dedicated to innovation in AI & Data. Our mission is to leverage cutting-edge technology to create impactful solutions that drive business success. We foster a collaborative and inclusive culture where creativity and teamwork thrive. About the Role We are seeking a highly skilled ML/AI Developer to join our growing team in India. This role involves developing machine learning and deep learning models, building conversational AI applications, and deploying solutions using cloud-native tools. Work Location : Hyderabad (hi-tech City). Shift Timings :EST Time Zone Experience : Min 5+yrs Responsibilities Design and deploy ML/AI models using CNN, RNN, Seq2Seq, and LLMs. Develop and fine-tune NLP-driven solutions and integrate them into chatbot platforms. Build chatbot solutions using Microsoft Bot Framework, Dialogflow, or OpenAI APIs. Preprocess and engineer datasets using Python for training and evaluation. Deploy AI models and services using AWS or Azure. Collaborate cross-functionally with engineering, product, and DevOps teams. Explore and apply RLHF, prompt engineering, and newer AI optimization strategies. Follow Agile development methodology and participate in sprints. Qualifications Bachelor’s or Master’s in ML Engineering (preferred) or Data Science. 5–6 years of experience in ML/AI engineering or data science roles. Strong Python programming skills. Solid knowledge of algorithms like KNN, SVM, Naive Bayes. Proven work with NLP, CNNs, LLMs, and deep learning architectures. Experience working with cloud platforms – AWS or Azure. Prior experience integrating chatbots or conversational AI in production. Required Skills Familiarity with Microsoft Bot Framework, Dialogflow, or OpenAI APIs. Knowledge of model versioning, monitoring, or MLOps practices. Bonus: Open-source contributions or AI research experience. Equal Opportunity Statement We are committed to diversity and inclusivity in our hiring practices. We encourage applications from individuals of all backgrounds and experiences.

Skill: NX/CAD Developer Experience: 3-6 Years Location: Bangalore Mode: Hybrid Notice Period: Immediate - 15 Days Job Summary: We are hiring NX/CAD Developers with 36 years of experience to join our engineering automation and CAD customization team. The ideal candidates should have hands-on experience with NXOpen API, CAD scripting, and CAD data handling using OpenJT. You will play a key role in customizing and automating NX functionalities to improve product development workflows. Key Responsibilities: Develop and maintain custom NX/CAD applications using NXOpen APIs (C#, C++, Python). Create automation scripts and tools to enhance design productivity. Customize the NX user interface, templates, and dialogs to suit business processes. Use XSLT for XML data transformation in CAD integrations. Work with OpenJT for handling lightweight 3D models and visualization tasks. Integrate NX applications with PLM systems like Teamcenter (desirable). Perform CAD tool enhancements, unit testing, documentation, and troubleshooting. Collaborate with design, manufacturing, and PLM teams to understand technical needs. Key Skills & Technologies: NXOpen: C#, C++, Python (preferred) Scripting: NX Journaling, Python, VBScript XSLT: Data transformation for CAD-PLM integrations OpenJT: Lightweight 3D visualization support Version Control: Git/SVN (preferred) Knowledge of CAD data structure, assemblies, and model configuration Preferred Qualifications: Bachelor’s or master’s degree in mechanical engineering, Computer Science, or related field Experience working in an Agile environment Exposure to PLM systems (e.g., Teamcenter) Good problem-solving and debugging skills with CAD toolchains

We are building a machine learning-based anomaly detection system using structured and sequential sensor data. The goal is to identify unusual patterns or faults through data modeling and visualization. This internship offers a real-world opportunity to work on machine learning pipelines and understand both supervised and unsupervised approaches to anomaly detection. This phase focuses on offline/static modeling using historical sensor data in tabular and time-series formats. 🎯 Internship Objective Analyze sensor datasets representing various operational scenarios Apply and evaluate supervised classification models Transition into unsupervised anomaly detection approaches Visualize insights and document findings for technical and non-technical audiences 📘 Key Responsibilities Perform data preprocessing: cleaning, encoding, normalization, and feature engineering Train And Evaluate Classification Models Using Artificial Neural Networks (ANN) Long Short-Term Memory (LSTM) models for sequence-based classification Explore And Implement Unsupervised Anomaly Detection Techniques Isolation Forest One-Class SVM Z-score or IQR-based statistical methods Analyze And Visualize Model Outputs Using Confusion matrices Anomaly heatmaps Time-series plots Optional: Build a lightweight dashboard (e.g., Streamlit) to present findings About Company: TechnoExcel is the leading training and consulting company in Hyderabad offering data analytics solutions.

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. Fraud/AML Risk Analytics Professional Job Specification Candidate would be responsible for developing, validating, auditing and maintaining AI/ML/NLP models for Fraud/AML/Credit risk. Candidates would be expected to support financial institutions on meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level 3-7 years of experience; Location: Bangalore Core Skill Requirements Requirements Candidate must have relevant experience in Machine Learning/Artificial Intelligence, Natural Language Programming, Statistical / Mathematical modeling, quantitative research, Fraud/AML risk management, or related Credit Risk field at a reputed bank, fintech, or a consulting firm. Wider skill requirements include: Experience in Machine learning algorithms like Random Forest, SVM, Neural Network etc. and Artificial Learning use cases such as Natural Language Processing, Robotics etc. AML Scenario development, enhancement. Initial threshold setting and tuning. Proficiency in one or more analytical tools such Python, PY Spark, Data Science and cloud-based analytics etc. Experience in Model Development, Model Validation, Model Audit (implementation and execution experience will not be considered directly relevant) Business knowledge in transaction monitoring system, sanction screening, trade surveillance. Supports and/or runs global/regional internal SMEs; responsible for investigating and researching the Financial Crimes processes and tools identifying efficiency and effectiveness opportunities. Strengthen AML knowledge, Process Governance & Controls. Support Regulatory exams, Internal Audit, Compliance Assurance test, Self-identified issues / findings. Identify, assess, actively manage and control the risks that could come from our business, operational and organizational decisions. Develop and leverage innovative features and algorithms to drive down false positives and identify perceived threat across the firm Utilize traditional statistical analytics, graph theory / network science, ensemble methods and the like Natural language processing, text analytics, factors analysis / construct development and testing, machine learning feature development and engineering, etc. Prior experience in domains like AML/ Financial Crime analytics and strong knowledge of fraud data analysis and development, strategy design and delivery deployment. Non-functional Skill Requirements In order to succeed in PwC Risk CoE, it is desirable for candidates to possess: Understanding of market trends and demands in the financial services sector and issues faced by clients by staying abreast of current business and industry trends relevant to the client's business Excellent oral and written communication skills Solid analytical and problem-solving skills; ability to isolate and solve issues using large amounts of data Process orientation with strong technical skills and attention to detail Deep technical capabilities and industry knowledge of financial products Willingness to travel to meet client needs, as needed Educational Background Desired candidate must have a master’s degree or higher in a quantitative discipline such as Economics, Statistics, Mathematics, Operation Research, Econometrics, Data Science, Finance, Engineering + MBA; advanced degree is a plus; Industry relevant certifications in CQF, FRM, CFA, CPA certification is a plus Additional Requirement For Senior Positions Candidates aspirant of senior positions at PwC Risk CoE are expected to possess: Proven consulting skills to structure vague problems at hand and conceptualizing solutions Credentials in leading and driving large and or complex risk analytics engagements and initiatives independently Experience in supporting sales pursuits for risk analytics offerings and solutions Ability to manage multiple engagements simultaneously along with leading people and initiatives Strong conceptual understanding of various functional/technical skills Ability to drive innovation and thought leadership in the risk management domain Intellectual property, patents and exclusive rights on any innovative solution is a plus

A career in our Model Risk and Validation practice, within Risk Data and Analytics services, will provide you with the opportunity to help our clients develop a strategic and sustainable approach to harness the value of their data and drive business results. We work with organisations across industries to develop customised, cost effective technology solutions that focus on delivering the relevant, actionable intelligence that executives need to understand operations and manage critical risks. As part of the team, you’ll help organisations manage the deployment and maintenance of complex models used for risk management and valuation. To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future. Fraud/AML Risk Analytics Professional Job Specification As a Senior Manager, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to: Candidate would be responsible for developing, validating, auditing and maintaining AI/ML/NLP models for Fraud/AML/Credit risk. Candidates would be expected to support financial institutions on meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level 12-15 years of experience; Location: Bangalore Core Skill Requirements Candidate must have relevant experience in Machine Learning/Artificial Intelligence, Natural Language Programming, Statistical / Mathematical modeling, quantitative research, Fraud/AML risk management, or related Credit Risk field at a reputed bank, fintech, or a consulting firm. Wider skill requirements include: Experience in Machine learning algorithms like Random Forest, SVM, Neural Network etc. and Artificial Learning use cases such as Natural Language Processing, Robotics etc. AML Scenario development, enhancement. Initial threshold setting and tuning. Proficiency in one or more analytical tools such Python, PY Spark, Data Science and cloud-based analytics etc. Experience in Model Development, Model Validation, Model Audit (implementation and execution experience will not be considered directly relevant) Business knowledge in transaction monitoring system, sanction screening, trade surveillance. Supports and/or runs global/regional internal SMEs; responsible for investigating and researching the Financial Crimes processes and tools identifying efficiency and effectiveness opportunities Strengthen AML knowledge, Process Governance & Controls. Support Regulatory exams, Internal Audit, Compliance Assurance test, Self-identified issues / findings. Identify, assess, actively manage and control the risks that could come from our business, operational and organizational decisions. Develop and leverage innovative features and algorithms to drive down false positives and identify perceived threat across the firm Utilize traditional statistical analytics, graph theory / network science, ensemble methods and the like Natural language processing, text analytics, factors analysis / construct development and testing, machine learning feature development and engineering, etc. Prior experience in domains like AML/ Financial Crime analytics and strong knowledge of fraud data analysis and development, strategy design and delivery deployment. Non-functional Skill Requirements In order to succeed in PwC Risk CoE, it is desirable for candidates to possess: Understanding of market trends and demands in the financial services sector and issues faced by clients by staying abreast of current business and industry trends relevant to the client's business Excellent oral and written communication skills Solid analytical and problem-solving skills; ability to isolate and solve issues using large amounts of data Process orientation with strong technical skills and attention to detail Deep technical capabilities and industry knowledge of financial products Willingness to travel to meet client needs, as needed Educational Background Desired candidate must have a master’s degree or higher in a quantitative discipline such as Economics, Statistics, Mathematics, Operation Research, Econometrics, Data Science, Finance, Engineering + MBA; advanced degree is a plus; Industry relevant certifications in CQF, FRM, CFA, CPA certification is a plus Additional Requirement Candidates aspirant of senior positions at PwC Risk CoE are expected to possess: Proven consulting skills to structure vague problems at hand and conceptualizing solutions Credentials in leading and driving large and or complex risk analytics engagements and initiatives independently Experience in supporting sales pursuits for risk analytics offerings and solutions Ability to manage multiple engagements simultaneously along with leading people and initiatives Strong conceptual understanding of various functional/technical skills Ability to drive innovation and thought leadership in the risk management domain Intellectual property, patents and exclusive rights on any innovative solution is a plus

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 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 Our Vision 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 3+ years of 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.

Job Summary We are looking for an experienced AI & Generative AI Developer who can work across the AI spectrum—from classical machine learning models to cutting-edge Generative AI applications. The role demands strong experience in building ML models using regression, classification, and tree-based algorithms, along with hands-on exposure to LLMs and generative frameworks like GPT, Stable Diffusion, and LangChain. Key Responsibilities 🔹 Classical AI/ML Design and implement supervised and unsupervised ML models including: Linear Regression, Logistic Regression Decision Trees, Random Forest, XGBoost Naive Bayes, K-Means, SVM, PCA, etc. Preprocess and analyse structured/tabular datasets Evaluate models using metrics like accuracy, precision, recall, ROC-AUC, and RMSE Build predictive models, deploy them into production, and monitor performance Collaborate with business teams to translate requirements into ML use cases 🔹 Generative AI (GenAI) Build and fine-tune LLMs (e.g., GPT, LLaMA, PaLM) for summarisation, Q&A, document generation, etc. Implement prompt engineering, RAG pipelines, and vector database integrations Use libraries like Hugging Face Transformers, LangChain, and LlamaIndex Develop APIs to expose GenAI models in real-time apps Optimise model inference using quantisation, batching, etc. Ensure safe, explainable, and bias-free output in alignment with AI ethics guidelines Required Skills & Qualifications Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or related field Strong programming skills in Python, with experience in NumPy, Pandas, Scikit-learn Proficiency in classical ML algorithms (regression, trees, naive Bayes, etc.) Experience with LLM frameworks like OpenAI API, Hugging Face, and LangChain Understanding of transformer architecture, NLP, embeddings, and tokenisation Familiarity with REST API development using FastAPI/Flask Exposure to cloud platforms (AWS/GCP/Azure) and Docker/Kubernetes Preferred / Nice To Have Experience with deep learning (TensorFlow, PyTorch) Exposure to image/audio/video generation using models like DALL·E, Stable Diffusion, Whisper Familiarity with RAG, LLMOps, and vector stores (FAISS, Pinecone, Weaviate) Knowledge of MLOps pipelines, model monitoring, and CI/CD for ML

Genpact is a global professional services and solutions firm with over 125,000 employees in 30+ countries. Driven by curiosity, entrepreneurial agility, and the desire to create value for clients, we serve leading enterprises worldwide with deep business knowledge, digital operations services, and expertise in data, technology, and AI. Our purpose is the relentless pursuit of a world that works better for people. We are currently seeking a Business Analyst - Data Scientist to join our team. In this role, you will be responsible for developing and implementing NLP models and algorithms, extracting insights from textual data, and working collaboratively with cross-functional teams to deliver AI solutions. Responsibilities: Model Development: - Proficiency in various statistical, ML, and ensemble algorithms - Strong understanding of Time series algorithms and forecasting use cases - Ability to evaluate model strengths and weaknesses for different problems Data Analysis: - Extracting meaningful insights from structured data - Preprocessing data for ML/AI applications Collaboration: - Working closely with data scientists, engineers, and business stakeholders - Providing technical guidance and mentorship to team members Integration and Deployment: - Integrating ML 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 on NLP techniques and tools to stakeholders Qualifications: Minimum Qualifications / Skills: - Bachelor's degree in computer science, Engineering, or a related field - Strong programming skills in Python and R - Experience with DS frameworks (SKLEARN, NUMPY) - Knowledge of machine learning concepts and frameworks (TensorFlow, PyTorch) - Strong problem-solving and analytical skills - Excellent communication and collaboration abilities Preferred Qualifications / Skills: - Experience in Predictive Analytics and Machine Learning techniques - Proficiency in Python/R/Any other open-source programming language - Knowledge of visualization tools such as Tableau, Power BI, Qlikview, etc. - Applied statistics skills - Experience with big data technologies (Hadoop, Spark) - Knowledge of cloud platforms (AWS, Azure, GCP) If you are passionate about leveraging your skills in data science and analytics to drive innovation and value creation, we encourage you to apply for this exciting opportunity at Genpact.,

Linux -VCS Knowledge & Experience / Qualifications (For the role not the role holder. Minimum requirements of the role.) Minimum Five Years of experience in UNIX/Linux Infrastructure. Expertise on Administration and troubleshooting of UNIX Operating System (Linux/Solaris/AIX) Great knowledge on VMWare, Symantec Storage Foundation, Veritas Cluster Server (Configuration/Troubleshooting) Troubleshooting of VERITAS Volume Manager, VERITAS Cluster Server and VERITAS Netbackup Client. Ability to develop UNIX Shell Script. Understating of LVM/SVM Understanding of Network OSI Model, TCP/IP and Routing. Good knowledge of RAID Levels such as RAID-0, RAID-1, RAID-1+0, RAID-5. Able to manage and configure EMC/Hitachi LUNs on UNIX (AIX/Solaris/Linux) servers. Understanding of multipath concept and its implementation as well. Communication and interpersonal skills. Client focused, Great Team and sharing spirit, autonomous and rigorous Effective time management Should possess industry standard certifications for UNIX domain. Should be well versed with ITIL concepts and more specific understanding of Service operations activities. Ability to work effectively as a team player. Working across cultures. Do Ensure timely response of all the tickets raised by the client end user Service requests solutioning by maintaining quality parameters Act as a custodian of clients network/ server/ system/ storage/ platform/ infrastructure and other equipments to keep track of each of their proper functioning and upkeep Keep a check on the number of tickets raised (dial home/ email/ chat/ IMS), ensuring right solutioning as per the defined resolution timeframe Perform root cause analysis of the tickets raised and create an action plan to resolve the problem to ensure right client satisfaction Provide an acceptance and immediate resolution to the high priority tickets/ service Installing and configuring software/ hardware requirements based on service requests 100% adherence to timeliness as per the priority of each issue, to manage client expectations and ensure zero escalations Provide application/ user access as per client requirements and requests to ensure timely solutioning Track all the tickets from acceptance to resolution stage as per the resolution time defined by the customer Maintain timely backup of important data/ logs and management resources to ensure the solution is of acceptable quality to maintain client satisfaction Coordinate with on-site team for complex problem resolution and ensure timely client servicing Review the log which Chat BOTS gather and ensure all the service requests/ issues are resolved in a timely manner Mandatory Skills: Veritas cluster Server. Experience: 3-5 Years.

Description year Of exp- 6 to 10 Years Location- Noida, Pune, Bangalore, Nagpur Requirements Job Requirements: 6+ years of experience in a Data Scientist role Strong analytic skills related to working with unstructured datasets. Strong understanding of statistical methods and hypothesis testing. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Experience supporting and working with cross-functional teams in a dynamic environment. Required Skills: Programming Languages: Proficiency in Python API / Framework: Hands-on experience with PySpark Data Manipulation: Strong experience with libraries like pandas, NumPy, dplyr, etc. Machine Learning: Hands-on experience with ML algorithms (regression, classification, clustering, etc.) Machine learning Models: Experience developing and tuning machine learning models such as Random Forest, Support Vector Machines (SVM), Natural Language Processing (NLP) techniques Cloud: Hands-on experience with AWS services for data science and ML, including S3 and EC2 Orchestration tool: Experience with orchestration tools like Luigi to manage data pipelines or ML workflows. Statistical Analysis: Solid foundation in probability, statistics, hypothesis testing, and experimental design (e.g., A/B testing). Data Visualization: Experience with visualization tools such Tableau, or Power BI. SQL & Databases: Ability to write complex SQL queries; familiarity with relational databases (PostgreSQL, MySQL, etc.). CICD: Experience with CI/CD practices and tools (GitHub) for automating data workflows and model deployments. Other Tool: Proficient in Microsoft Excel for exploratory data analysis, reporting, and data validation. Soft Skills: – Strong problem-solving and critical thinking abilities. – Excellent communication skills to explain technical concepts to non-technical stakeholders. – Ability to work independently and collaboratively in a fast-paced, agile environment. – Detail-oriented, with a focus on data quality and accuracy. Good To have: Domain Knowledge. Job responsibilities Collaborate with data engineers, analysts, and business stakeholders to understand requirements and deliver solutions. Monitor model performance and retrain as needed to ensure accuracy and reliability. Collect, clean, and preprocess large datasets from various sources. Develop statistical models and machine learning algorithms to solve business problems. Stay updated with the latest industry trends, tools, and technologies. What we offer Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally. Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today. Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way! High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do. About GlobalLogic GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.

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 Our Vision 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 3+ years of 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 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. 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