629 Xgboost Jobs - Page 7

The Data Science and AI/ML team collaborates across the organization to identify, develop and deliver Artificial Intelligence (AI) and Machine Learning (ML) powered software solutions that improve patient outcomes, delight partners and customers, and enhance business operations in an AI First fashion. The team works on projects ranging from building sophisticated models to delivering personalized recommendations to patients, analyzing sleep data to optimize equipment and settings, proactively identifying health risk factors, and optimizing global supply chain operations. As a Sr. Machine Learning Engineer, you will play a crucial role in contributing to and leading the development of ML architecture and operations. Your responsibilities include optimizing time to market and quality of AI/ML applications by working on projects within the AI operations team. You will ensure that global AI/ML systems are production-grade, scalable, and utilize cutting-edge technology and methodology. Additionally, you will collaborate with stakeholders, mentor junior team members, and engage with business stakeholders. Key Responsibilities: - Collaborate with Product Management, Engineering, and other stakeholders to create impactful AI/ML features and products. - Work closely with Data Scientists and Data Engineers to own the end-to-end process, train junior team members, and maintain AI/ML architectures. - Document model design, experiments, tests, and outcomes, and stay informed of industry trends. - Implement process improvements, build production-level AI/ML systems, and support technical issues for stakeholders. - Participate in Code Review and handle escalated incidents to resolution. Requirements: - 4+ years of industry experience in Machine Learning Engineering, Data Science, or Data Engineering. - M.S or PhD in Data Science/Machine Learning or related areas. - Proficiency in data analytics systems development, model building, and online deployment. - Experience in building scalable AI/ML systems for various advanced problems. - Hands-on experience with large datasets, Python, and cloud-based tools. - Strong mathematical foundation and knowledge of machine learning techniques. Joining the team means more than just a job it's an opportunity to be part of a culture that values excellence, diversity, and innovation. If you are looking for a challenging and supportive environment where your ideas are encouraged, apply now to be a part of our team dedicated to making the world a healthier place. We are committed to reviewing every application we receive.,

Project Role : Full Stack Engineer Project Role Description : Responsible for developing and/or engineering the end-to-end features of a system, from user experience to backend code. Use development skills to deliver innovative solutions that help our clients improve the services they provide. Leverage new technologies that can be applied to solve challenging business problems with a cloud first and agile mindset. Must have skills : Data Science Good to have skills : NA Minimum 3 Year(s) Of Experience Is Required Educational Qualification : 15 years full time education Summary: As a Full Stack Engineer, you will be responsible for developing and engineering the end-to-end features of a system. Your typical day will involve collaborating with cross-functional teams to design and implement innovative solutions that enhance user experience and optimize backend processes. You will leverage new technologies to address complex business challenges while maintaining a cloud-first and agile approach, ensuring that the services provided to clients are continuously improved and aligned with their needs. Your role will require a balance of creativity and technical expertise to deliver high-quality software solutions that meet project requirements and client expectations. Roles & Responsibilities: - Expected to perform independently and become an SME. - Required active participation/contribution in team discussions. - Contribute in providing solutions to work related problems. - Collaborate with team members to design and implement new features. - Conduct code reviews to ensure quality and adherence to best practices. "• Experience with Hugging Face Transformers, LangChain, OpenAI APIs • Strong knowledge of machine learning libraries: scikit-learn, XGBoost, LightGBM • Experience with Retrieval-Augmented Generation (RAG): Faiss, Pinecone, Weaviate, ChromaDB • Training, fine-tuning, and optimizing transformer models (BERT, GPT, T5, LLaMA) • Deep understanding of self-attention, positional embeddings, sequence modeling • Strong NLP expertise: Named Entity Recognition (NER), topic modeling, text embeddings • Good grasp of linear algebra: vectors, matrices, eigenvalues, eigenvectors etc • Expertise in gradient descent, backpropagation, activation functions, loss functions • Experience with dimensionality reduction techniques for feature selection • Knowledge of time-series forecasting, anomaly detection, and probabilistic modeling • Understanding of model serving techniques, including REST APIs and real-time inference" "• Develop and fine-tune LLMs (GPT, BERT, T5, LLaMA, Mistral) for text generation, summarization, translation, and question-answering tasks. • Work with transformer-based architectures, understanding self-attention mechanisms, token embeddings, and model interpretability. • Implement custom tokenization techniques, text embedding models (Sentence-BERT, OpenAI Embeddings, Cohere, etc.), and efficient inference optimizations. • Apply prompt engineering and prompt tuning techniques to optimize model responses. • Work with LangChain and LLM orchestration frameworks to build AI-powered applications. • Build Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, Weaviate, ChromaDB. • Work with Hugging Face Transformers, spaCy, NLTK, and OpenAI APIs." Professional & Technical Skills: - Must To Have Skills: Proficiency in Python (Programming Language). - Good To Have Skills: Experience with JavaScript frameworks such as React or Angular. - Strong understanding of RESTful API design and development. - Familiarity with cloud platforms such as AWS or Azure. - Experience with database management systems like MySQL or PostgreSQL. "Must Have Skills: 1. Must have 5-7+ years of experience working as a Microsoft FED Angular. 2. Strong understanding of software development principles, design patterns, and best practices. 3. Develop, test, and maintain software applications using Angular and .NET. 4. Designing & developing user interfaces using angular best practices 5. Developing application code & unit tests in angular. 6. Experience in consuming Web API/ Rest API using Javascript. 7. Should have good troubleshooting and debugging skills Good to Have Skills: 1. Knowledge/Experience in Excel 2 Knowledge/Experience of Agile methodology and Sprint based project delivery Nice to Have Skills: 1. .Net Core 2. Agile Development Methodology 2. MySQL" "• Should be good team player. • Good Written & Verbal Communication skills • Good analytical and troubleshooting skills." Additional Information: - The candidate should have minimum 3 years of experience in Python (Programming Language). - This position is based at our Bengaluru office. - A 15 years full time education is required. Resource should be open to work in B Shift (Afternoon Shifts 12:30 to 10:30) during week days., 15 years full time education

Job Title: Senior Data Scientist Location: Kolkata/Bangalore (Remote/Hybrid options available) Company: Inxite-out Job Overview: We are seeking a highly skilled and experienced Senior Data Scientist to join our dynamic team. This role will involve leading data science initiatives, developing advanced machine learning models, and providing actionable insights for business strategies. The ideal candidate will have a strong background in data science, statistical analysis, and business problem-solving, with a passion for delivering high-quality solutions. Key Responsibilities & Skills: Lead the development of advanced predictive and prescriptive models using machine learning, forecasting and other statistical methods Working knowledge of regression, classification, clustering, association algorithms and model optimization techniques Work closely with business stakeholders to understand requirements and translate them into data science solutions Design and implement end-to-end data science workflows, including data collection, preprocessing, feature engineering, model building, and evaluation Collaborate with cross-functional teams to deploy and integrate models into production environments Perform model validation, fine-tuning, and optimization to ensure accuracy and scalability Identify and investigate anomalies or unexpected behaviours in model outputs Build REST APIs using Fast/Flask, move models into production, ensure expected accuracies and throughput for the model Mentor and guide junior data scientists, providing technical expertise and leadership Qualifications: Bachelors or master’s in computer science, Statistics, Mathematics, Engineering, or a related field 4+ years of experience in data science or a similar analytical role, with a proven track record of delivering impactful projects Strong proficiency in python with experience in libraries like pandas, NumPy, Spacy, TensorFlow, Scikit-learn etc. Experience in working with cloud platforms (Azure), Databricks, PySpark Strong theoretical and practical knowledge of ML model development, hyper-parameter tuning, and production deployment Solid understanding of statistical analysis, data mining, feature engineering Strong problem-solving skills with the ability to think critically and adapt to complex business challenges Excellent communication skills with the ability to explain complex data-driven concepts to a non-technical audience Experience in leading and mentoring junior team members. Strong understanding of MLOps- lifecycle of a machine learning model Additional Skills (good to have): Knowledge of deep learning, CNN, MLP, OpenCV etc. Working knowledge of NLP/GenAI based solutions Experience working with SAP (S/4 HANA, BW) is a plus

Management Level: Ind & Func AI Decision Science Consultant Location: Gurgaon, Mumbai, Bangalore Must-have skills: Risk Analytics, Model Development, Validation, and Auditing, Performance Evaluation, Monitoring, Governance, Statistical Techniques:Linear Regression, Logistic Regression, GLM, GBM, XGBoost, Time Series (ARMA/ARIMA), Programming Languages:SAS, R, Python, Spark, Scala, Tools:Tableau, PowerBI, Regulatory Knowledge:Basel/CCAR/DFAST/CECL/IFRS9, Risk Reporting and Dashboard Solutions Good to have skills: Advanced Data Science Techniques, AML, Operational Risk Modelling, Cloud Platform Experience (AWS/Azure/GCP), Machine Learning Interpretability and Bias Algorithms Job Summary We are seeking a highly skilled Ind & Func AI Decision Science Consultant to join the Accenture Strategy & Consulting team in the Global Network Data & AI practice. You will be responsible for risk model development, validation, and auditing activities, ensuring performance evaluation, monitoring, governance, and documentation. This role offers opportunities to work with top financial clients globally, utilizing cutting-edge technologies to drive business capabilities and foster innovation. Roles & Responsibilities: Engagement Execution Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation, and end-to-end delivery of risk solutions for Accentures clients. Ability to manage workstreams of small projects, overseeing the quality of deliverables for junior team members. Demonstrated ability to manage day-to-day interactions with client stakeholders. Practice Enablement Guide junior team members. Support development of the practice by driving innovations and initiatives. Develop thought leadership and disseminate information around current and emerging trends in Risk. Professional & Technical Skills: 2-6 years of relevant Risk Analytics experience at one or more Financial Services firms or Professional Services/Risk Advisory with significant exposure to Credit Risk: PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting, Revenue Forecasting Models, IFRS9/CECL Loss Forecasting across Retail and Commercial portfolios. Credit Acquisition/Behavior: Modeling, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios. Regulatory Capital and Economic Capital Models Liquidity Risk: Liquidity Models, Stress Testing Models, Basel Liquidity Reporting Standards Anti-Money Laundering (AML): AML Scenarios/Alerts, Network Analysis Operational Risk: AMA Modeling, Operational Risk Reporting Modeling Techniques: Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time Series (ARMA/ARIMA), ML Interpretability and Bias Algorithms Programming Languages & Tools: SAS, R, Python, Spark, Scala, Tableau, QlikView, PowerBI, SAS VA Strong understanding of Risk functions and their application in client discussions and project implementation. Additional Information: Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities. Industry Certifications:FRM, PRM, CFA preferred. Excellent Communication and Interpersonal Skills. About Our Company | Accenture Qualification Experience: Minimum 2-6 years of relevant Risk Analytics experience, Exposure to Financial Services firms or Professional Services/Risk Advisory Educational Qualification: Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities, Industry certifications such as FRM, PRM, CFA preferred

Job Description First Solar reserves the right to offer you a role most applicable to your experience and skillset. Basic Job Functions: This position manages organizational strategy and operations through design and statistical analysis of business initiatives and experiments. Works with business partners to understand what the business needs and issues are to address. Applies advanced knowledge of statistics and data mining (e.g., predictive modelling, simulation) or other mathematical techniques to recognize patterns and create insights from business data. Designs, develops, and evaluates statistical and predictive models that lead to business solutions. Serves as lead statistician for the unit, providing expertise, oversight, and guidance on statistical analysis efforts. Communicate findings and recommendations to management across different departments. Supports implementation efforts. Should lead and mentor the team working in the Data Competency Centre. Education/Experience: Bachelor’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 8-10 years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development Master’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 5+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development PhD degree in Data Science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 4+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development Working knowledge of budgets and financial statements Required Skills/Competencies: Demonstrated skill of managing teams; Ability to coach and mentor team members to drive results Demonstrated experience with programming languages and statistical software tools (Python, SAS, R, JMP or similar), relational databases (SQL server), data analysis and visualization software (preferably PowerBI, SAS). Demonstrated experience with standard data science and machine learning packages such as Numpy, Pandas, Matplotlib, seaborn, bokeh, plotly Demonstrated experience with the machine learning model stack (regression, classification, neural networks, time series) and packages (Scikit learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels) Demonstrated experience of the machine learning model tradeoffs such as hyper-parameter tuning, regularization, cross-validation, skewness in data, dimensionality reduction, and complexity vs interpretability. Demonstrated experience with utilizing advanced descriptive statistics and analysis techniques (such as forecasting, analysis of variance, t-tests, categorical data analysis, nonparametric data analysis, cluster analysis, factor analysis and multivariate statistical analysis) design business experiments and measure the impact of business actions. Demonstrated experience with computer vision models (e.g. image classification, object detection, and segmentation) Demonstrated experience working with various business partners to scope and design the statistical framework for business solutions and socialize and help integrate results. Strong communication skills to work with groups, and experience with communicating business implications of complex data relationships and results of statistical models to multiple business partners. Essential Responsibilities: Statistical Analysis & Model Development Works with business partners to identify and scope new opportunities for statistical analysis applications to evaluate business performance and to support business decisions. Works internally and with I/S and Enterprise Data Management to define, secure and prepare datasets for statistical modeling. Explores data using a variety of statistical (e.g., data mining, regression, cluster analysis) techniques to answer business questions or guide future model development. Build programs for running statistical tests on data and for understanding correlation of various attributes. Builds hypotheses, identifies research data attributes and determines the best approach to address business issues. Working with business partners leads development of experimental design for business initiatives. Applies advanced statistical techniques, including analysis of variance, t-tests, factor analysis, regression and multivariate analyses or simulation, to analyze the effects of business initiatives. Build predictive models (e.g. logistic regression, generalized linear models) as appropriate to support business partner objectives. Builds and deploys computer vision models (e.g., image classification, object detection, segmentation) to meet business needs. Prepares testing scenarios and tests model performance. Incorporates findings and provides insights as part of model development and enhancement. Provides guidance and direction related to statistical analysis to less experienced Data Science & Analytics staff as needed. Provides peer review related to analytics methods and results. Responsible for advanced analytics, including experimental design and analysis, for the most complex business experiments. Model Consultation, Implementation, & Communication Serves as statistical expert within the unit as well as in consultation to various areas of the business, to support design and analysis of business experiments. Leads analytics projects or components related to large, complex business initiatives. Prepare recommendations and findings for business partners. Works with research and analytics staff and other areas of the business on model application and implementation. Effectively communicates and delivers statistical and predictive model results to business partners, supporting socialization and adoption of analysis results into business activities and decisions. Assists with knowledge transfer and training to business areas regarding new analytics applications as part of implementation process. Works closely with business stakeholders to identify and answer critical questions. Assists in the development of standard analytical approaches and methodologies for the department. Provides knowledge transfer and training on new modeling and statistical analysis tools and methodologies to less experienced staff. Industry Research Research and maintain awareness of industry’s best practices and business strategies. Proactively brings in new and innovative ideas and approaches to develop business solutions. Research and leverage new statistical techniques and technologies to apply in their statistical research work. Reporting Relationships: Will report to Head- Automation Digital Transformation USA This role will have direct reports Travel: Physical Requirements: Will sit and stand for long periods of time during the day. Will walk, climb stairs and on equipment. May reach above shoulder heights and below the waist May lift up to 50 lbs. Required to use hands to finger, lift, handle, carry or feel objects. May stoop, kneel, bend, talk and hear. Specific vision abilities are required. All associates working on the production floor may be required to wear a respirator at any given time and thus, the ability to wear a respirator is a condition of employment and continued employment (require little or no facial hair). Office Physical Requirements: All positions in our office require interaction with people and technology while either standing or sitting. To best service our customers, internal and external, all associates must be able to communicate face-to-face and on the phone with or without reasonable accommodation. First Solar is committed to compliance with its obligations under all applicable state and federal laws prohibiting employment discrimination. In keeping with this commitment, it attempts to reasonably accommodate applicants and employees in accordance with the requirements of the disability discrimination laws. It also invites individuals with disabilities to participate in a good faith, interactive process to identify reasonable accommodations that can be made without imposing an undue hardship. Potential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role. All candidates receiving an offer of employment must successfully complete a background check and any other tests that may be required. Equal Opportunity Employer Statement: First Solar is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company. I have read and understand the above ‘Roles and Responsibilities’ for this position. I believe I meet the ‘Minimum Qualifications’ to perform the required ‘Essential Functions & Responsibilities’ to the best of my abilities.

Step into the world of AI innovation with the Experts Community of Soul AI (By Deccan AI). We are looking for India’s top 1% Data Scientists for a unique job opportunity to work with the industry leaders. Who can be a part of the community? We are looking for top-tier Data Scientists with expertise in predictive modeling, statistical analysis, and A/B testing. If you have experience in this field then this is your chance to collaborate with industry leaders. What’s in it for you? Pay above market standards The role is going to be contract based with project timelines from 2 - 12 months , or freelancing. Be a part of an Elite Community of professionals who can solve complex AI challenges. Work location could be: Remote (Highly likely) Onsite on client location Deccan AI’s Office: Hyderabad or Bangalore Responsibilities: Lead design, development, and deployment of scalable data science solutions optimizing large-scale data pipelines in collaboration with engineering teams. Architect advanced machine learning models (deep learning, RL, ensemble) and apply statistical analysis for business insights. Apply statistical analysis, predictive modeling, and optimization techniques to derive actionable business insights. Own the full lifecycle of data science projects—from data acquisition, preprocessing, and exploratory data analysis (EDA) to model development, deployment, and monitoring. Implement MLOps workflows (model training, deployment, versioning, monitoring) and conduct A/B testing to validate models. Required Skills: Expert in Python, data science libraries (Pandas, NumPy, Scikit-learn), and R with extensive experience with machine learning (XGBoost, PyTorch, TensorFlow) and statistical modeling. Proficient in building scalable data pipelines (Apache Spark, Dask) and cloud platforms (AWS, GCP, Azure). Expertise in MLOps (Docker, Kubernetes, MLflow, CI/CD) along with strong data visualization skills (Tableau, Plotly Dash) and business acumen. Nice to Have: Experience with NLP, computer vision, recommendation systems, or real-time data processing (Kafka, Flink). Knowledge of data privacy regulations (GDPR, CCPA) and ethical AI practices. Contributions to open-source projects or published research. What are the next steps? 1. Register on our Soul AI website. 2. Our team will review your profile. 3. Clear all the screening rounds: Clear the assessments once you are shortlisted. As soon as you qualify all the screening rounds (assessments, interviews) you will be added to our Expert Community! 4. Profile matching and Project Allocation: Be patient while we align your skills and preferences with the available project. Skip the Noise. Focus on Opportunities Built for You!

Job Location: Hyderabad / Bangalore / Pune Immediate Joiners / less than 30 days About the Role We are looking for a seasoned AI/ML Solutions Architect with deep expertise in designing and deploying scalable AI/ML and GenAI solutions on cloud platforms. The ideal candidate will have a strong track record in BFSI, leading end-to-end projects—from use case discovery to productionization—while ensuring governance, compliance, and performance at scale. Key Responsibilities Lead the design and deployment of enterprise-scale AI/ML and GenAI architectures. Drive end-to-end AI/ML project delivery : discovery, prototyping, productionization. Architect solutions using leading cloud-native AI services (AWS, Azure, GCP). Implement MLOps/LLMOps pipelines for model lifecycle and automation. Guide teams in selecting and integrating GenAI/LLM frameworks (OpenAI, Cohere, Hugging Face, LangChain, etc.). Ensure robust AI governance, model risk management , and compliance practices. Collaborate with senior business stakeholders and cross-functional engineering teams. Required Skills & Experience 15+ years in AI/ML, cloud architecture, and data engineering. At least 10 end-to-end AI/ML project implementations. Hands-on expertise in one or more of the following: ML frameworks: scikit-learn, XGBoost, TensorFlow, PyTorch GenAI/LLM tools: OpenAI, Cohere, LangChain, Hugging Face, FAISS, Pinecone Cloud platforms: AWS, Azure, GCP (AI/ML services) MLOps: MLflow, SageMaker Pipelines, Kubeflow, Vertex AI Strong understanding of data privacy, model governance, and compliance frameworks in BFSI. Proven leadership of cross-functional technical teams and stakeholder engagement.

skills in Python, with experience in ML libraries like Tensor Flow, PyTorch, Scikit-learn, XGBoost,AWS, Azure, or GCP and cloud-native ML tools (SageMaker, Vertex AI, Azure ML)Docker, Kubernetes,MLOps, model monitoring, Spark, Hadoop, Hive

As a Data Scientist, you will be responsible for building cutting-edge models using NLP, ML, and AI techniques to solve a variety of problems across different domains. Your main tasks will include working closely with the engineering team to deploy models in production, validating the models, and ensuring their effectiveness. You should possess expert-level knowledge in Natural Language Processing, Information Extraction, Scraping, and Text Mining Algorithms, as well as a strong familiarity with deep learning methods for text analytics. Proficiency in Machine Learning algorithms such as XGBoost, Linear Regression, Logistic Regression, SVM, Random Forest, Bayesian Methods, Unsupervised Learning, and Reinforcement Learning is essential for this role. Additionally, experience in time series analysis with real-world datasets, familiarity with technologies like Flask, FastAPI, and Hug, and being an expert Python programmer are key requirements for this position. You should have a proven track record of expertise demonstrated through high-quality publications, competitions, or challenges. Collaboration with domain experts, a passion for making a meaningful impact, and strong problem-solving skills are highly valued attributes. A minimum qualification of B.E/B.Tech in Computer Science, Electrical Engineering, or EXTC with a solid foundation in mathematics and statistics is necessary. Excellent communication skills, teamwork abilities, and the capacity to thrive in a startup environment are also essential for success in this role. In this role, you will be expected to take care of Text Analytics on Qualitative Customer Feedback and Call Center complaints conversations via Email or Chat. The ideal candidate should have 2 to 8 years of relevant experience, with a salary ranging from 15 Lac to 18 Lac P.A. The industry focus is on Analytics and Business Intelligence. If you are a Data Scientist with expertise in Core Python, Machine Learning, and a strong interest in an internship, this opportunity is perfect for you. Walk-ins are welcome for candidates who meet the specified qualifications and key skills outlined above.,

First Solar reserves the right to offer you a role most applicable to your experience and skillset. Basic Job Functions: This position manages organizational strategy and operations through design and statistical analysis of business initiatives and experiments. Works with business partners to understand what the business needs and issues are to address. Applies advanced knowledge of statistics and data mining (e.g., predictive modelling, simulation) or other mathematical techniques to recognize patterns and create insights from business data. Designs, develops, and evaluates statistical and predictive models that lead to business solutions. Serves as lead statistician for the unit, providing expertise, oversight, and guidance on statistical analysis efforts. Communicate findings and recommendations to management across different departments. Supports implementation efforts. Should lead and mentor the team working in the Data Competency Centre. Education/Experience: Bachelor’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 8-10 years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development Master’s degree in data science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 5+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development PhD degree in Data Science, Computer science, Electrical Engineering, Applied Statistics, or Physics with 4+ years of relevant work experience in Data Science, Artificial Intelligence or Machine Learning algorithm development Working knowledge of budgets and financial statements Required Skills/Competencies: Demonstrated skill of managing teams; Ability to coach and mentor team members to drive results Demonstrated experience with programming languages and statistical software tools (Python, SAS, R, JMP or similar), relational databases (SQL server), data analysis and visualization software (preferably PowerBI, SAS). Demonstrated experience with standard data science and machine learning packages such as Numpy, Pandas, Matplotlib, seaborn, bokeh, plotly Demonstrated experience with the machine learning model stack (regression, classification, neural networks, time series) and packages (Scikit learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels) Demonstrated experience of the machine learning model tradeoffs such as hyper-parameter tuning, regularization, cross-validation, skewness in data, dimensionality reduction, and complexity vs interpretability. Demonstrated experience with utilizing advanced descriptive statistics and analysis techniques (such as forecasting, analysis of variance, t-tests, categorical data analysis, nonparametric data analysis, cluster analysis, factor analysis and multivariate statistical analysis) design business experiments and measure the impact of business actions. Demonstrated experience with computer vision models (e.g. image classification, object detection, and segmentation) Demonstrated experience working with various business partners to scope and design the statistical framework for business solutions and socialize and help integrate results. Strong communication skills to work with groups, and experience with communicating business implications of complex data relationships and results of statistical models to multiple business partners. Essential Responsibilities: Statistical Analysis & Model Development Works with business partners to identify and scope new opportunities for statistical analysis applications to evaluate business performance and to support business decisions. Works internally and with I/S and Enterprise Data Management to define, secure and prepare datasets for statistical modeling. Explores data using a variety of statistical (e.g., data mining, regression, cluster analysis) techniques to answer business questions or guide future model development. Build programs for running statistical tests on data and for understanding correlation of various attributes. Builds hypotheses, identifies research data attributes and determines the best approach to address business issues. Working with business partners leads development of experimental design for business initiatives. Applies advanced statistical techniques, including analysis of variance, t-tests, factor analysis, regression and multivariate analyses or simulation, to analyze the effects of business initiatives. Build predictive models (e.g. logistic regression, generalized linear models) as appropriate to support business partner objectives. Builds and deploys computer vision models (e.g., image classification, object detection, segmentation) to meet business needs. Prepares testing scenarios and tests model performance. Incorporates findings and provides insights as part of model development and enhancement. Provides guidance and direction related to statistical analysis to less experienced Data Science & Analytics staff as needed. Provides peer review related to analytics methods and results. Responsible for advanced analytics, including experimental design and analysis, for the most complex business experiments. Model Consultation, Implementation, & Communication Serves as statistical expert within the unit as well as in consultation to various areas of the business, to support design and analysis of business experiments. Leads analytics projects or components related to large, complex business initiatives. Prepare recommendations and findings for business partners. Works with research and analytics staff and other areas of the business on model application and implementation. Effectively communicates and delivers statistical and predictive model results to business partners, supporting socialization and adoption of analysis results into business activities and decisions. Assists with knowledge transfer and training to business areas regarding new analytics applications as part of implementation process. Works closely with business stakeholders to identify and answer critical questions. Assists in the development of standard analytical approaches and methodologies for the department. Provides knowledge transfer and training on new modeling and statistical analysis tools and methodologies to less experienced staff. Industry Research Research and maintain awareness of industry’s best practices and business strategies. Proactively brings in new and innovative ideas and approaches to develop business solutions. Research and leverage new statistical techniques and technologies to apply in their statistical research work. Reporting Relationships: Will report to Head- Automation Digital Transformation USA This role will have direct reports Travel: Physical Requirements: Will sit and stand for long periods of time during the day. Will walk, climb stairs and on equipment. May reach above shoulder heights and below the waist May lift up to 50 lbs. Required to use hands to finger, lift, handle, carry or feel objects. May stoop, kneel, bend, talk and hear. Specific vision abilities are required. All associates working on the production floor may be required to wear a respirator at any given time and thus, the ability to wear a respirator is a condition of employment and continued employment (require little or no facial hair). Office Physical Requirements: All positions in our office require interaction with people and technology while either standing or sitting. To best service our customers, internal and external, all associates must be able to communicate face-to-face and on the phone with or without reasonable accommodation. First Solar is committed to compliance with its obligations under all applicable state and federal laws prohibiting employment discrimination. In keeping with this commitment, it attempts to reasonably accommodate applicants and employees in accordance with the requirements of the disability discrimination laws. It also invites individuals with disabilities to participate in a good faith, interactive process to identify reasonable accommodations that can be made without imposing an undue hardship. Potential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role. All candidates receiving an offer of employment must successfully complete a background check and any other tests that may be required. Equal Opportunity Employer Statement: First Solar is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company. I have read and understand the above ‘Roles and Responsibilities’ for this position. I believe I meet the ‘Minimum Qualifications’ to perform the required ‘Essential Functions & Responsibilities’ to the best of my abilities. Job Identification 1021960 Job Category NPI-HSRT Integration Data Science Posting Date 07/17/2025, 12:17 AM Job Schedule Full time Locations Plot No.A-1/1 SIPCOT Industrial Park, Sriperumbudur, Tamil Nadu, 602105, IN Work Schedule Normal Shift New (PMT)

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 you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As a ML Developer at EY GDS Assurance Digital, you will be responsible for leveraging advanced machine learning techniques to develop innovative, high-impact models and solutions that drive growth and deliver significant business value. You will be helping EY's sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. This is a full-time Machine Learning Developer role, responsible for building and deploying robust machine learning models to solve real-world business problems. You will be working on the entire ML lifecycle, including data analysis, feature engineering, model training, evaluation, and deployment. Requirements: - A bachelor's degree (BE/BTech/MCA & MBA) in Computer Science, Engineering, Information Systems Management, Accounting, Finance, or a related field with adequate industry experience. - Technical skills requirements include developing and implementing machine learning models, conducting exploratory data analysis (EDA), applying dimension reduction techniques, utilizing statistical models, evaluating and validating models, solid background in Python, familiarity with Time Series Forecasting, basic experience with cloud platforms such as AWS, Azure, or GCP, and exposure to ML Ops tools and practices (e.g., MLflow, Airflow, Docker). Additional skill requirements: - Proficient at quickly understanding complex machine learning concepts and utilizing technology for tasks such as data modeling, analysis, visualization, and process automation. - Skilled in selecting and applying the most suitable standards, methods, tools, and frameworks for specific ML tasks and use cases. - Capable of collaborating effectively within cross-functional teams, while also being able to work independently on complex ML projects. - Demonstrates a strong analytical mindset and systematic approach to solving machine learning challenges. - Excellent communication skills, able to present complex technical concepts clearly to both technical and non-technical audiences. Join us in building a better working world at EY, where opportunities for personal development, skill advancement, and career progression await. Be part of a diverse team of professionals dedicated to creating long-term value for clients, people, and society while fostering trust in the capital markets. Apply now and be a part of our journey towards a better future.,

As an Artificial Intelligence Specialist at Gen AI, you will be responsible for driving customer conversations, understanding customer requirements, creating Gen AI solution architectures, and developing customer proposals and RFP responses. You will guide solution engineers in creating Gen AI POCs and solutions for various industry verticals. Your role will involve staying updated on the latest technology developments, industry best practices, and incorporating them into Gen AI applications. Additionally, you will design and deploy Proof of Concepts (POCs) and Points of View (POVs) across different industry verticals to showcase the potential of Generative AI applications. To qualify for this role, you should have at least 8 years of experience in software development, with a minimum of 3 years of experience in Generative AI solution development. A bachelor's degree or higher in Computer Science, Software Engineering, or related fields is required. You should be adept at critical thinking, logical reasoning, and have a strong ability to learn new industry domains quickly. Being a team player who can deliver under pressure is essential. Furthermore, you should have experience with cloud technologies such as Azure, AWS, or GCP, as well as a good understanding of NVIDIA or similar technologies. A solid appreciation of AI/ML concepts and sound design principles is necessary for this role. In terms of required skills, you should be extremely dynamic and enthusiastic about technology. Development experience with languages like C++, Java, JavaScript, HTML, C#, Python, or node.js is preferred. You should be able to adapt quickly to new challenges and evolving technology stacks. Excellent written and verbal communication skills in English are essential, along with strong analytical and critical thinking abilities. A customer-focused attitude, initiative-taking, self-driven nature, and the ability to learn quickly are also important qualities for this role. Knowledge of Python, ML Algorithms, Statistics, source code maintenance, versioning tools, Object-Oriented Programming Concepts, debugging, and analytical skills is required. Preferred skills for this position include at least 5 years of experience in ML development and MLOps. Strong programming skills in Python, knowledge of ML, Data, and API libraries, and expertise in creating end-to-end data pipelines are advantageous. Experience with ML models, ModelOps/MLOps, AutoML, AI Ethics, Trust, Explainable AI, and popular ML frameworks like SparkML, TensorFlow, scikit-learn, XGBoost, H2O, etc., is beneficial. Familiarity with working in cloud environments (AWS, Azure, GCP) or containerized environments (Mesos, Kubernetes), interest in understanding functional and industry business challenges, and knowledge of IT industry and GenAI use cases in insurance processes are preferred. Expertise in Big Data and Data Modeling is also desirable for this role.,

Do you want to be a part of a team that is revolutionizing the global economy Join the dynamic Data & Decision Science (D&DS) team at C2FO, a leading online platform for working capital with a presence in over 160 countries and serving more than $10.5 trillion in annual sales. Based in Kansas City, C2FO has a global workforce of over 500 employees and operates in various regions including Europe, India, Asia Pacific, and Australia. At C2FO, we prioritize the quality of our technical solutions and are committed to building innovative solutions to address business challenges effectively. We also place a strong emphasis on maintaining a healthy work-life balance and fostering a culture of continuous learning. Our team encourages participation in hackathons, book clubs, and supports a remote-first work environment, ensuring that your voice is heard and your contributions make a real impact. The Data & Decision Science team at C2FO is a multifaceted and collaborative group consisting of Data Engineering, Data Science & Analytics, Data Operations, and Business Intelligence pillars. With a presence in India and the US, our team plays a crucial role in driving C2FO's global growth by developing scalable data solutions and promoting data-driven innovation. As a Senior Data Scientist at C2FO, you will have the opportunity to work on a diverse set of challenges ranging from traditional machine learning applications like forecasting and credit scoring to cutting-edge uses of large language models (LLMs) for customer engagement and retention. You will operate in a fast-paced environment that values initiative, ownership, and curiosity. Key Responsibilities: - Develop machine learning models and scalable data solutions for critical business problems such as dynamic discounting, customer retention, and credit scoring - Design and iterate on minimum viable products (MVPs) to address real business pain points - Collaborate across teams to translate complex business challenges into data science problems - Ensure data validation and quality by working closely with Data Engineering and Data Governance teams - Conduct in-depth analyses to derive actionable insights from complex datasets - Foster a culture of learning, innovation, and experimentation Qualifications: - 5+ years of hands-on experience in data science or applied machine learning - Proficiency in mathematics, statistics, and machine learning concepts - Experience deploying machine learning models in production environments - Strong skills in Python, SQL, Pandas, and relevant data manipulation tools - Familiarity with libraries such as Scikit-learn, XGBoost, PyTorch, etc. - Experience in hypothesis testing and experimentation frameworks - Strong problem-solving, communication, and stakeholder management abilities - Bonus: Background in fintech or financial services At C2FO, we prioritize the well-being of our employees and offer a comprehensive benefits package, flexible work options, volunteer time off, and more. We are committed to fostering diversity and inclusion, empowering our team members to bring their authentic selves to work and contribute to our shared success. Join us in creating a workplace that reflects the diversity of our communities and clients worldwide.,

As a Senior Data Scientist specializing in Generative AI at our organization, you will play a crucial role in driving technical innovation and delivering impactful results within a team setting. You will be responsible for working with financial data, applying NLP techniques, refining prompt engineering strategies for LLMs, collaborating with stakeholders, developing and testing Python code for GenAI solutions, integrating with vector databases, monitoring MLOps pipelines, researching emerging GenAI technologies, and troubleshooting and debugging GenAI models in production. To excel in this role, you must possess a Master's degree in Computer Science, Data Science, or a related field, with a Ph.D. being preferred. You should have 8-12 years of experience in a Data Scientist or equivalent role, with at least 4 years of specialized experience in Generative AI. Additionally, you should have demonstrable experience in the full lifecycle of real-world, production-level GenAI project implementation. You must stay up-to-date with the rapidly evolving GenAI landscape, continuously learn and explore new tools and techniques, and effectively communicate technical concepts to non-technical stakeholders. Proficiency in Python, along with expertise in key libraries for AI/ML and GenAI applications such as TensorFlow, PyTorch, and Transformers, is mandatory. Experience in designing and implementing scalable API architectures for GenAI applications, along with a deep understanding of Machine Learning concepts, is essential. Preferred qualifications for this role include experience with MLOps, cloud computing platforms, conversational AI solutions, and contributions to research and publications in the field of Generative AI. As a Senior Data Scientist, you will be expected to demonstrate strong technical leadership and mentorship skills, as well as excellent communication and collaboration abilities. This job description provides a comprehensive overview of the responsibilities and qualifications required for the Senior Data Scientist position. If you are a highly motivated individual with a strong passion for Generative AI and possess the necessary technical skills and experience, we encourage you to apply for this role.,

Moniepoint is Africa's all-in-one financial ecosystem, empowering businesses and their customers with seamless payment, banking, credit, and management tools. In 2023, we processed $182 billion and are Nigeria’s largest merchant acquirer. Your Opportunity and Mission We are looking for talented and passionate Data Scientist to join the Growth team. Data science and optimization are key drivers for Moniepoint’s business growth and the Data Scientist joining will have the opportunity to build and own the most important models starting from our attribution and Marketing Mix Models Contribute the following areas: channel attribution modeling, mCAC per channel modeling, LTV prediction, Marketing Mix Modeling and multichannel attribution and testing Develop, test and own our production marketing attribution models for better budgeting and increased marketing efficiency Develop, test and productionize attribution and predictive algorithms by using state of the art machine learning algorithms and optimisation models Design experiments and interpret the results to draw detailed and actionable conclusions Work in cross-functional teams across disciplines such as product, engineering and business. You Have... +5 years of professional experience outside of an academic and internship setting, in a quantitative analysis role in top companies. FMCG or Fintech preferred. Holds at least an MSc, and preferably a PhD in a scientific discipline such as Physics, Statistics, Engineering, Computer Science or Mathematics Deep theoretical and applied knowledge in the following areas: statistical inference, bayesian statistics, causal inference, time series analysis and mathematical optimisation. Extensive experience at least in Multichannel Attribution Modeling and Marketing Mix Modeling Extensive experience in statistical programming (Python) and experience working with popular tools such as Pandas, SciPy, XGBoost, Jupyter/iPython notebooks and well-known modeling packages such as PyMC3 Extensive experience with the end-to-end predictive/prescriptive model development cycle, from problem definition to productionalization and maintenance. This includes excellent data modeling and SQL skills, and familiarity with Cloud infrastructure. Demonstrated experience in designing and analyzing experiments in digital products (A/B test, multivariate, etc.) Experience with the application of statistical modeling and advanced analytics to provide product-shaping insights Excellent spoken and written English What Moniepoint Can Offer You The opportunity to drive financial inclusion and shape the future of the African financial ecosystem The chance to work on innovative and impactful projects A dynamic, diverse, and collaborative environment where every team member’s voice is recognized and valued Flexible work arrangements Continuous learning and career growth opportunities Competitive salary, individual performance bonuses, and firmwide performance bonus Company covered health insurance plans Pension plans What To Expect In The Hiring Process A preliminary phone call with one of our recruiters A general interview with the Senior Manager of Marketing Strategy A case study-based discussion with SVP of Marketing A behavioural interview with members of the Executive team Moniepoint is an equal-opportunity employer. We believe diversity makes us stronger and are committed to creating an inclusive environment for all employees and candidates.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. The Defender Experts (DEX) Research team is at the forefront of Microsoft’s threat protection strategy, combining world-class hunting expertise with AI-driven analytics to protect customers from advanced cyberattacks. Our mission is to move protection left—disrupting threats early, before damage occurs—by transforming raw signals into intelligence that powers detection, disruption, and customer trust. We’re looking for a passionate and curious Data Scientist to join this high-impact team. In this role, you'll partner with researchers, hunters, and detection engineers to explore attacker behavior, operationalize entity graphs, and develop statistical and ML-driven models that enhance DEX’s detection efficacy. Your work will directly feed into real-time protections used by thousands of enterprises and shape the future of Microsoft Security. This is an opportunity to work on problems that matter—with cutting-edge data, a highly collaborative team, and the scale of Microsoft behind you. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Design and build robust, large-scale graph structures to model security entities, behaviors, and relationships. Develop and deploy scalable, production-grade AI/ML systems and intelligent agents for real-time threat detection, classification, and response. Collaborate closely with Security Research teams to integrate domain knowledge into data science workflows and enrich model development. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Work with large-scale graph data: create, query, and process it efficiently to extract insights and power models. Lead initiatives involving Graph ML, Generative AI, and agent-based systems, driving innovation across threat detection, risk propagation, and incident response. Collaborate closely with engineering and product teams to integrate solutions into production platforms. Mentor junior team members and contribute to strategic decisions around model architecture, evaluation, and deployment. Qualifications Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field 5+ years of experience applying data science or machine learning in a real-world setting, preferably in security, fraud, risk, or anomaly detection Proficiency in Python and/or R, with hands-on experience in data manipulation (e.g., Pandas, NumPy), modeling (e.g., scikit-learn, XGBoost), and visualization (e.g., matplotlib, seaborn) Strong foundation in statistics, probability, and applied machine learning techniques Experience working with large-scale datasets, telemetry, or graph-structured data Ability to clearly communicate technical insights and influence cross-disciplinary teams Demonstrated ability to work independently, take ownership of problems, and drive solutions end-to-end Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? Model Risk Management Group (MRMG) is responsible for the model risk management of all American Express models. The role will report to Head of MRMG and lead some of India teams to manage enterprise-wide model risk. The successful candidate will be responsible to manage and control model risk in order to elevate model excellence, strengthen long term shareholder value, and adapt to the changing landscape of both model development innovation, external environment and heightened regulatory expectations. Responsibilities include: Oversee and own independent validation of enterprise-wide models including marketing models Lead visionary research to explore opportunities to elevate model excellence and drive business impact Oversee and support regulatory and audit examinations Effectively communicate key outcomes of model risk management activities to senior management, business partners and regulators Take timely actions to ensure a consistent high-level performance in line with the company’s winning framework and priorities Motivate staff and leaders across teams to deliver at optimal levels. Qualifications: Core competencies at leading roles related to model risk management or statistical modeling to deal with complex business problems Proven people leadership experience with the ability to lead, motivate and mentor highly competent and multi-layered teams, dispersed geographically Demonstrated ability and project leadership to lead large scale MRM initiatives Exceptional ability to build, leverage, and maintain relationships with senior leaders, business partners, and regulators Proven record of designing strategies and communicating effectively to bring senior management and diverse stakeholders on board. Experience with managing regulators, working with external/ internal auditors preferred. Understand the evolving compliance and regulatory requirements with key focus on gaps to stabilize and eliminate vulnerabilities in MRM Deep understanding in Machine Learning models (e.g., Gradient Boosting Machine, XGBoost, and Neural Network) as well as classic statistical modeling techniques and assumptions Degree with quantitative background or equivalent experience Must Have: 10+ years of work experience Must have worked in a GSIB in the field of model risk Good in-depth understanding of machine learning techniques like GBM, Random Forest etc. Should have modeling experience on marketing models. Need to have the aptitude to read research papers and turn them into actionable items for MRM (bring external perspective) Aptitude to think independently to come up with innovative solutions We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

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.

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Description Summary: What you need to know about the role- Data scientists are highly motivated team players with strong analytical skills who specialize in creating, driving and executing initiatives to mitigate fraud on PayPal’s platform and improve the experience for PayPal’s hundreds of millions of customers, while guaranteeing compliance with regulations. Meet our team Data scientists in the Fraud Risk team are problem solvers suited to approach varied challenges in complex big data environments. Our core goals are to enable seamless and delightful experiences to our customers, while preventing threat actors from accessing customers’ financial instruments and personal information. As part of our day-to-day job, we are collaborating with a wide variety of partners: product owners, data scientists, security experts, legal consults, and engineers, to bring our data science insights to life, impacting the experience and security of millions of customers around the globe. Job Description: Your way to impact Data scientists deeply understand PayPal’s business objectives, as their impact on PayPal’s top and bottom lines is immense. As a data scientist, you will develop key AIML capabilities, tools, and insights with the aim of adapting PayPal’s advanced proprietary fraud prevention and experience mechanisms and enabling growth. Your day to day Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets. What Do You Need To Bring- Strong proficiency in Python for data analysis, machine learning, and automation. Solid understanding of supervised and unsupervised AI/machine learning methods (e.g., XGBoost, LightGBM, Random Forest, clustering, isolation forests, autoencoders, neural networks, transformer-based architectures). Experience in payment fraud, AML, KYC, or broader risk modeling within fintech or financial institutions. Experience developing and deploying ML models in production using frameworks such as scikit-learn, TensorFlow, PyTorch, or similar. Hands-on experience with LLMs (e.g., OpenAI, LLaMA, Claude, Mistral), including use of prompt engineering, retrieval-augmented generation (RAG), and agentic AI to support internal automation and risk workflows. Ability to work cross-functionally with engineering, product, compliance, and operations teams. Proven track record of translating complex ML insights into business actions or policy decisions. BS/BA degree with 5+ years of related professional experience or master’s degree with 4+ years of related experience. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply. REQ ID R0127046

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.

Data Science Engineering Consultant Responsibilities : Own development of the applications, ensuring focus on correctness, resilience and quality Troubleshoot system problems, conduct thorough impact analysis of any changes across different application within Business Intelligence. Take ownership of the full software development lifecycle, from initial discussions through to design, development, testing, deployment. Create detailed technical specifications and test case documents including results of regression testing for all changes. Design and implement data models to support various business needs, including analytics, reporting, and machine learning. Should be able to communicate and collaborate with global teams. Provide expert advice and design inputs in the areas of Data Modelling, Data Warehousing, Data Marts, Data Governance, and Security. Mandatory Requirements: Bachelor’s degree in computer science or a related field (graduate). 5-8 years plus relevant industry experience. Proficient in Python, AI/ML, SQL and/or any other scripting language. Experience in developing and tuning LLMs or GenAI Models (GPT, LLaMA, Claude) Strong proficiency in python and libraries such as LangChain, HayStack, Transformers. Good Experience in Machine Learning and training models using XGBoost, Neural Networks, Random Forests, Scikit-Learn, Pandas. Experience conducting Exploratory Data Analysis (EDA) to identify trends and patterns, report key metrics. Good to have Tableau/Visualization Experience to integrate/deploy trained models to Analytics Suite. Have hands-on experience with at least 1 end to end implementation cycle of a data science project. Strong knowledge of statistical analysis and modelling techniques. Experience with Cloud Data Lake technologies such as Snowflake. Desirable Requirements Nice to have AI&ML certification. Working Knowledge of various analytics application such as Informatica for ETL. Tableau including installation/upgrade of Tableau. Knowledge of Documentation and collaboration tools (Confluence, SharePoint, JIRA). Comfortable working in Agile methodology and full SDLC process. Excellent interpersonal, communication and team building skills with ability to explain complex topics clearly. Self-motivated with pro-active approach. flexibility to work on multiple items, open minded and willing to contribute to an individual capacity. Working knowledge on Gitlab CI/CD is required.

Role Data Science Engineering Consultant Responsibilities Own development of the applications, ensuring focus on correctness, resilience and quality Troubleshoot system problems, conduct thorough impact analysis of any changes across different application within Business Intelligence. Take ownership of the full software development lifecycle, from initial discussions through to design, development, testing, deployment. Create detailed technical specifications and test case documents including results of regression testing for all changes. Design and implement data models to support various business needs, including analytics, reporting, and machine learning. Should be able to communicate and collaborate with global teams. Provide expert advice and design inputs in the areas of Data Modelling, Data Warehousing, Data Marts, Data Governance, and Security. Mandatory Requirements Bachelor’s degree in computer science or a related field (graduate). 5-8 years plus relevant industry experience. Proficient in Python, AI/ML, SQL and/or any other scripting language. Experience in developing and tuning LLMs or GenAI Models (GPT, LLaMA, Claude) Strong proficiency in python and libraries such as LangChain, HayStack, Transformers. Good Experience in Machine Learning and training models using XGBoost, Neural Networks, Random Forests, Scikit-Learn, Pandas. Experience conducting Exploratory Data Analysis (EDA) to identify trends and patterns, report key metrics. Good to have Tableau/Visualization Experience to integrate/deploy trained models to Analytics Suite. Have hands-on experience with at least 1 end to end implementation cycle of a data science project. Strong knowledge of statistical analysis and modelling techniques. Experience with Cloud Data Lake technologies such as Snowflake. Desirable Requirements Nice to have AI&ML certification. Working Knowledge of various analytics application such as Informatica for ETL. Tableau including installation/upgrade of Tableau. Knowledge of Documentation and collaboration tools (Confluence, SharePoint, JIRA). Comfortable working in Agile methodology and full SDLC process. Excellent interpersonal, communication and team building skills with ability to explain complex topics clearly. Self-motivated with pro-active approach. flexibility to work on multiple items, open minded and willing to contribute to an individual capacity. Working knowledge on Gitlab CI/CD is required. Skills: cloud data lake,langchain,data warehousing,claude,gitlab,analytics,xgboost,data marts,data analysis,neural networks,sdlc,python,reporting,statistical analysis,analytics suite,ai/ml,haystack,sharepoint,data governance,llama,jira,llms,security,transformers,agile,genai models,machine learning,tableau,random forests,regression testing,exploratory data analysis,data modelling,pandas,gpt,gitlab ci/cd,sql,snowflake,informatica,confluence,scikit-learn,ai&ml certification

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.

As an AI/ML Manager at our Pune location, you will be responsible for leading the development of machine learning proof of concepts (PoCs) and demos using structured/tabular data for various use cases like forecasting, risk scoring, churn prediction, and optimization. Your role will involve collaborating with sales engineering teams to understand client requirements and presenting ML solutions during pre-sales calls and technical workshops. You will be expected to build ML workflows using tools such as SageMaker, Azure ML, or Databricks ML, managing training, tuning, evaluation, and model packaging. Applying supervised, unsupervised, and semi-supervised techniques like XGBoost, CatBoost, k-Means, PCA, and time-series models will be a key part of your responsibilities. Working closely with data engineering teams, you will define data ingestion, preprocessing, and feature engineering pipelines using Python, Spark, and cloud-native tools. Packaging and documenting ML assets for scalability and transition into delivery teams post-demo will be essential. Staying updated with the latest best practices in ML explainability, model performance monitoring, and MLOps practices is also expected. Participation in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes are additional aspects of this role. To qualify for this position, you should have at least 8+ years of experience in developing and deploying classical machine learning models in production or PoC environments. Strong hands-on experience with Python, pandas, scikit-learn, and ML libraries like XGBoost, CatBoost, LightGBM is required. Familiarity with cloud-based ML environments such as AWS SageMaker, Azure ML, or Databricks is preferred. A solid understanding of feature engineering, model tuning, cross-validation, and error analysis is necessary. Experience with unsupervised learning, clustering, anomaly detection, and dimensionality reduction techniques will be beneficial. You should be comfortable presenting models and insights to both technical and non-technical stakeholders during pre-sales engagements. Working knowledge of MLOps concepts, including model versioning, deployment automation, and drift detection, will be an advantage. If you are interested in this opportunity, please apply or share your resume at kanika.garg@austere.co.in.,

The Applications Development Intermediate Programmer Analyst position at our organization entails actively participating in the establishment and execution of new or modified application systems and programs in collaboration with the Technology team. Your primary goal in this role is to contribute to applications systems analysis and programming activities. Your responsibilities will include utilizing your knowledge of applications development procedures and concepts, as well as basic understanding of other technical areas, to identify and define necessary system enhancements. This will involve using script tools, analyzing code, and interpreting code. You will also be expected to consult with users, clients, and various technology groups to address issues, suggest programming solutions, and provide installation and support for customer exposure systems. Additionally, applying fundamental knowledge of programming languages for design specifications and analyzing applications to identify vulnerabilities and security issues will be part of your role. You will also be responsible for conducting testing, debugging, and serving as an advisor or coach to new or lower-level analysts. Your role will require you to identify problems, analyze information, and make evaluative judgments to recommend and implement solutions. You will need to resolve issues by identifying and selecting solutions through the application of acquired technical experience and guided by precedents. Furthermore, you should be able to operate with a limited level of direct supervision, exercise independence of judgment and autonomy, and act as a subject matter expert to senior stakeholders and/or other team members. It is crucial that you appropriately assess risk when making business decisions and demonstrate particular consideration for the firm's reputation and safeguarding Citigroup, its clients, and assets. Key Responsibilities: - Design and implement ETL pipelines using PySpark and Big Data tools on platforms like Hadoop, Hive, HDFS, etc. - Write scalable Python code for Machine Learning preprocessing tasks and work with libraries such as pandas, Scikit-learn, etc. - Develop data pipelines to support model training, evaluation, and inference. Skills required for this role include proficiency in Python programming with experience in PySpark for large-scale data processing, hands-on experience in Big Data technologies such as Hadoop, Hive, HDFS, exposure to machine learning workflows, model lifecycle, and data preparation, experience with ML libraries like Scikit-learn, XGBoost, Tensorflow, PyTorch, and exposure to cloud platforms (AWS/GCP) for data and AI workloads. Qualifications: - 4-8 years of relevant experience in the Financial Service industry - Intermediate level experience in Applications Development role - Demonstrated clear and concise written and verbal communication skills - Proven problem-solving and decision-making abilities - Ability to work under pressure, manage deadlines, and adapt to unexpected changes in expectations or requirements Education: - Bachelor's degree/University degree or equivalent experience This job description serves as a comprehensive overview of the primary responsibilities and requirements for the role. Other job-related duties may be assigned as necessary.,