Manager - Data Scientist

About the job

Ready to shape the future of work At Genpact, we don't just adapt to change-we drive it. AI and digital innovation are redefining industries, and we're leading the charge. Genpact's AI Gigafactory, our industry-first accelerator, is an example of how we're scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies' most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that's shaping the future, this is your moment.Genpact (NYSE:G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Responsibilities. Model Development & Statistical Analysis - Design, develop, and optimize machine learning, deep learning, and statistical models to solve complex business problems. GenAI & LLM Integration - Implement and integrate AI/ML models into GenAI and Agentic AI applications using LangChain, LangGraph, OpenAI APIs, RAG pipelines, and vector databases. End-to-End ML Pipelines - Build, deploy, and maintain scalable ML pipelines, from data ingestion and preprocessing to model deployment, monitoring, and lifecycle management. Production Deployment & MLOps - Deploy models as APIs or services using Docker, Kubernetes, FastAPI, and cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML) while implementing CI/CD for automated testing and versioning. Performance Monitoring & Reliability - Monitor model performance in production, detect drift or degradation, and establish alerting mechanisms to ensure reliability, compliance, and governance. Analytics Integration - Embed models into real-time dashboards and analytics applications to deliver actionable insights for business and HR stakeholders. Governance & Compliance - Ensure model explainability (XAI), security, audit logging, and adherence to ethical, regulatory, and enterprise standards. Knowledge Sharing - Conduct and participate in training sessions, workshops, and technical discussions to share insights, AI/ML techniques, and best practices with team members. Stakeholder Communication - Translate complex model results, analytics, and AI-driven insights into clear, actionable recommendations for business and non-technical stakeholders. Documentation & Enablement - Create well-structured documentation, reproducible workflows, and explanatory reports to support model adoption, operational handovers, and team learning. Cross-Functional Collaboration - Works closely with senior data scientists, engineers, and product teams to implement AI/ML solutions, ensuring alignment with project requirements and business objectives. Independent Contribution - Executes tasks such as data cleaning, exploratory analysis, feature engineering, and baseline model development under guidance, contributing to end-to-end AI/ML workflows. Stakeholder Alignment - Assists in presenting findings, visualizations, and insights to business and HR stakeholders, translating technical results into actionable recommendations. Qualifications We Seek in YouMinimum Qualifications / Skills. Bachelor's or Master's degree in data science, Computer Science, Statistics, Mathematics, or a related quantitative field. Years of hands-on experience in data analysis, machine learning, or AI projects, preferably in corporate or academic settings. Certification in areas like GenAI, Databricks etc. Preferred Qualifications / Skills. Hands-on experience in data preprocessing, exploratory data analysis, and feature engineering to support ML and AI model development. Knowledge of machine learning, deep learning, and NLP techniques for classification, regression, clustering, and predictive modelling. Proficiency in Python, SQL, ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn), and familiarity with cloud platforms (AWS, Azure, GCP) and data visualization tools. Experience integrating models into dashboards, analytics tools, and prototype AI applications. Familiarity with MLOps practices, model monitoring, CI/CD workflows, and cloud platforms (AWS, Azure, GCP). Ability to translate business problems into data-driven solutions and communicate insights to stakeholders effectively.

Requirements

• Machine Learning
• Data Science
• Statistical Analysis
• Python

Qualifications

• Bachelor's or Master's degree in data science
• Computer Science
• Statistics
• Mathematics

Preferred Technologies

• Machine Learning
• Data Science
• Statistical Analysis
• Python

About the company

Genpact is an advanced technology services and solutions company.