Sr. Data Scientist 4B

Job description

Sr. Data Scientist 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 We are looking for an experienced Data Scientist/Data Analytics Expert to support the client by developing, enhancing, and optimizing predictive analytics solutions for collections and customer engagement. Key Responsibilities • Design, develop, validate, and deploy machine learning models for collections analytics. • Perform data exploration, feature engineering, model training, validation, and performance monitoring. • Build scalable and production-ready machine learning pipelines. • Collaborate with business stakeholders, data engineers, and analytics teams to translate business requirements into analytical and machine learning solutions. • Evaluate and improve model performance using appropriate machine learning techniques and evaluation metrics. • Document model development processes, assumptions, methodologies, and deployment artifacts. • Support continuous model monitoring and enhancements based on business feedback and performance. Required Skills • Strong hands-on experience in Machine Learning, predictive analytics, and statistical modeling. • Proficiency in Python and machine learning libraries/frameworks such as Scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, or PyTorch. • Experience in feature engineering, model evaluation, hyperparameter tuning, and model explainability. • Strong understanding of supervised learning techniques, including classification, regression, and ensemble methods. • Hands-on experience with SQL and working with large structured datasets. • Good understanding of model deployment, monitoring, and MLOps practices. Preferred Skills • Experience in the Banking, Financial Services (BFSI), or Collections domain. • Hands-on experience developing machine learning or advanced analytics solutions for collections, customer engagement, or risk management. • Experience working on one or more of the following use cases:• Propensity to Pay • Best Time to Call • Right-Party Contact • Contact Strategy Optimization • Customer Segmentation or Behavioral Modeling • Exposure to cloud platforms such as AWS, Azure, or GCP is an added advantage. • Familiarity with GenAI/LLMs is a plus; however, the primary requirement is strong expertise in traditional Machine Learning and predictive analytics. Domain Experience (Highly Preferred) Candidates with prior experience in Collections Analytics will be strongly preferred. Knowledge of collections strategies, delinquency management, customer repayment behavior, contact optimization, and debt recovery analytics will be a significant advantage. Experience • Relevant years of overall experience in Data Science, Advanced Analytics, or Machine Learning. • Proven experience in building and deploying end-to-end machine learning solutions in production environments Qualifications Bachelors - Business Analytics, Bachelors - Computer Science, Bachelors - Statistics, Masters - Data Science Certifications Alteryx Designer Core Certification - Alteryx AcademyAlteryx Academy, Certificate in Deep Learning - Dimensionless TechademyDimensionless Techademy, Professional Machine Learning Engineer - InterPediaInterPedia Required Skills Adaptive Technology, Adaptive Technology, Agile Methodology, Amazon SageMaker, Anticipatory Capability, Artificial Intelligence (AI), Asset Management, Automated Machine Learning (AutoML), CI/CD, Client Relations, Collaboration Tools, Computer Vision, Context Awareness, Continuous Delivery, Continuous Integrations, Continuous Testing, Data Provisioning, Data Validation, Design Thinking, Embedded Systems, Executive Presence, Inclusion, Internet of Things (IoT), Machine Learning Model Management, Model Validation {+ 6 more} Language English Language Proficiency - Proficient - C2 Additional