Job at a glance
AI Engineer Ready to turn bold ideas into real-world impact? At Genpact, we don’t just adapt to change, we lead it. AI and digital innovation are transforming the way businesses work, and we’re at the forefront of it. Genpact’s AI Gigafactory , our industry-first accelerator, exemplifies how we scale advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale.
Whether tackling complex challenges through large-scale models or agentic AI , our breakthrough solutions tackle companies’ most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment. Genpact (NYSE: G) is an agentic and advanced technology solutions company.
We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world’s leading enterprises. Get to know us at genpact.com and on LinkedIn , YouTube , X , and Facebook .
Job Description Key Responsibilities: Data Analysis and Exploration: Employ advanced statistical techniques (e.g., hypothesis testing, regression analysis, time series analysis) to rigorously analyze large and complex datasets. Utilize data manipulation and cleaning techniques to ensure data quality, accuracy, and consistency. Develop and implement exploratory data analysis (EDA) strategies to identify patterns, trends, anomalies, and potential relationships within data.
Model Development and Deployment: Design, develop, and implement predictive models using a variety of machine learning algorithms (e.g., linear regression, decision trees, random forests, neural networks). Employ feature engineering techniques to optimize model performance and accuracy. Collaborate with data engineers to deploy models into production environments, ensuring scalability and maintainability.
Develop and maintain comprehensive documentation for models, including assumptions, methodology, and performance metrics. Data Visualization and Storytelling: Create compelling visualizations (e.g., dashboards, charts, graphs) to effectively communicate complex data findings to both technical and non-technical audiences. Develop data-driven narratives that translate insights into actionable recommendations for clients.
Present findings to clients and internal teams, highlighting key takeaways and implications for decision-making. Technical Expertise and Innovation: Stay abreast of the latest advancements in data science, machine learning, and statistical modeling techniques. Continuously explore and experiment with new algorithms, tools, and frameworks to enhance the efficiency and effectiveness of data analysis and modeling.
Contribute to the development of new methodologies, best practices, and internal knowledge-sharing initiatives. Model Performance Monitoring and Optimization: Monitor deployed models for performance, accuracy, data drift, and bias to ensure ongoing reliability and relevance. Conduct regular model evaluations and retraining as needed to maintain alignment with changing data patterns and business requirements.
Troubleshoot model and pipeline issues in collaboration with engineering teams to ensure stable and efficient production systems. Implement version control, validation, and testing practices to support reproducibility and continuous improvement. Qualifications we seek in you! Minimum Qualifications Master's or Ph.D. in a quantitative field such as Statistics, Mathematics, Computer Science, Data Science, or a related discipline.
Demonstrated experience in data science, machine learning, or statistical modeling. Proficiency in Python, Scala or R for data analysis, manipulation, a