Lead Data Scientist

Lead Data Scientist role at Capgemini, focused on delivering AI and predictive solutions across customer engagement, decision optimization, and responsible GenAI use cases.

Responsibilities

• Develop and deploy AI-driven solutions across customer engagement, personalization, recommendation, decision optimization, and customer insights.
• Partner with business stakeholders to apply advanced AI/ML tools and platforms to solve business problems.
• Build end-to-end solution capabilities spanning model development, deployment, evaluation, and scalability across AI use cases.
• Design and operationalize responsible AI systems as part of AI solution delivery.
• Drive AI/ML initiatives across multiple customer engagement and decision optimization scenarios.

Requirements

• Master’s or Ph.D. degree in Computer Science, Data Science, Operations Research, Statistics, Applied Mathematics, or a related discipline.
• 10+ years of prior work experience in Artificial Intelligence, Machine Learning, Data Science, Advanced Analytics, or related technical fields.
• Experience with unsupervised and supervised machine learning, including predictive modeling and propensity models.
• Hands-on experience with recommender systems, deep learning, and graph-based learning techniques.
• Experience working with advanced NLP frameworks (Transformers, etc.), GenAI solutions, and LLMs.
• Experience formulating and solving optimization problems.
• Knowledge of model evaluation, tuning, performance measurement, deployment practices, and solution scalability.
• Strong verbal and written communication skills, including presenting findings to both business and technical teams.
• Strong hands-on capability building predictive machine learning models, recommender systems, ranking models, and prescriptive optimization models.
• Proficiency in Python, SQL, MLOps, and modern AI/ML frameworks including scikit-learn, TensorFlow, PyTorch, and Hugging Face.
• Experience using AWS SageMaker and similar platforms for AI/ML delivery.
• Expertise across the AI/ML lifecycle: experimentation, A/B testing, feature engineering, model development, deployment, monitoring, measurement, and governance.
• Experience evaluating, deploying, and governing GenAI solutions, including RAG, knowledge retrieval, agentic AI workflows, LLM fine-tuning, and LLM evaluation frameworks.

Technologies

• Python, SQL, MLOps
• Scikit-learn, TensorFlow, PyTorch, Hugging Face, AWS SageMaker
• Transformers, LLMs, RAG
• GenAI, A/B testing
• Graph-based learning techniques, recommender systems
• Deep learning, propensity models, feature engineering

Nice to Have

• Experience applying ML, DL, Econometric and Foundation Models for time series forecasting.
• Experience working with knowledge graphs and graph-based learning approaches.
• Experience with constraint and mathematical programming, optimization packages, and solvers (IBM ILOG CPLEX, Gurobi, Google OR-Tools, etc.).

Benefits

• Flexible work
• Healthcare including dental, vision, mental health, and well-being programs
• Financial well-being programs such as 401(k) and Employee Share Ownership Plan
• Paid time off and paid holidays
• Paid parental leave
• Family building benefits including adoption assistance, surrogacy, and cryopreservation
• Social well-being benefits such as subsidized back-up child/elder care and tutoring
• Mentoring, coaching and learning programs
• Employee Resource Groups
• Disaster Relief
• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days depending on grade; Company paid holidays; Personal Days; Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs

Salary Transparency

• Base salary range for the tagged location: $110,841 to $145,000 per year.
• This role may be eligible for additional compensation, including variable compensation, bonus, or commission.
• Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and other benefits to eligible employees.

Location: Brooklyn, NY (hybrid)