Senior Data Scientist

Capgemini • Brooklyn, NY

1d • $80,420 - $106,050 • Hybrid

About The Position

Capgemini is hiring a Senior Data Scientist to develop and deploy AI-driven solutions for customer engagement, personalization, recommendation, decision optimization, and customer insights. The position is part of a multidisciplinary AI research and development environment, where the successful candidate will work with business stakeholders and a team of researchers and practitioners, using diverse data sources and advanced AI/ML tools and platforms to address business problems and deliver customer and business outcomes.

The role calls for expertise in predictive modeling, personalization, recommender systems, optimization, generative AI, and responsible AI systems. It is based in Westlake, Texas; Burlington, Massachusetts; or Durham, North Carolina, with a day-one onsite and hybrid arrangement.

The posted base salary range is $80,420–$106,050 per year. The role may also be eligible for variable compensation, bonuses, or commissions. Capgemini describes a comprehensive benefits package for eligible regular, full-time employees; specific availability depends on local policy and eligibility.

Requirements

• Master's or Ph.D. degree in Computer Science, Data Science, Operations Research, Statistics, Applied Mathematics, or a related discipline.
• At least 5 years of work experience in Artificial Intelligence, Machine Learning, Data Science, Advanced Analytics, or related technical fields.
• Experience with unsupervised and supervised machine learning, predictive modeling, propensity models, recommender systems, deep learning, and graph-based learning techniques.
• Experience with advanced NLP frameworks such as Transformers, generative AI solutions, and large language models.
• Experience formulating and solving optimization problems.
• Knowledge of model evaluation, tuning, performance measurement, deployment, and solution scalability.
• Strong verbal and written communication and presentation skills, including the ability to communicate effectively with business and technical teams.
• Strong hands-on experience building predictive machine learning models, recommender systems, ranking models, and prescriptive optimization models.
• Strong proficiency in Python, SQL, MLOps, and modern AI/ML development frameworks and platforms such as Scikit-learn, TensorFlow, PyTorch, Hugging Face, and AWS SageMaker.
• Expertise across the AI/ML lifecycle, including experimentation, A/B testing, feature engineering, model development, deployment, monitoring, measurement, and governance.
• Experience evaluating, deploying, and governing generative AI solutions, including RAG, knowledge retrieval, agentic AI workflows, LLM fine-tuning, and LLM evaluation frameworks.

Nice To Haves

• Experience applying machine learning, deep learning, econometric, and foundation models to time-series forecasting.
• Experience working with knowledge graphs and graph-based learning approaches.
• Experience with constraint or mathematical programming, optimization packages, and solvers such as IBM ILOG CPLEX, Gurobi, or Google OR-Tools.

Responsibilities

• Develop and deploy AI-driven solutions for customer engagement, personalization, recommendation, decision optimization, and customer insights.
• Work closely with business stakeholders and a team of researchers and practitioners to solve business problems using advanced AI/ML tools and platforms.
• Build predictive machine learning, recommender, ranking, and prescriptive optimization models.
• Conduct experimentation, A/B testing, feature engineering, model development, deployment, monitoring, measurement, and governance across the AI/ML lifecycle.
• Evaluate, deploy, and govern generative AI solutions, including retrieval-augmented generation, knowledge retrieval, agentic AI workflows, LLM fine-tuning, and LLM evaluation frameworks.
• Evaluate and tune models, measure performance, and support deployment and solution scalability.
• Communicate and present effectively to technical and business teams.

Benefits

• Flexible work.
• Healthcare coverage and programs, including dental, vision, mental health, and well-being programs.
• Financial well-being programs, including 401(k) and an Employee Share Ownership Plan.
• Paid time off and paid holidays.
• Paid parental leave.
• Family-building benefits, including adoption assistance, surrogacy, and cryopreservation.
• Subsidized backup childcare or elder care and tutoring.
• Mentoring, coaching, and learning programs.
• Employee Resource Groups.
• Medical, dental, and vision coverage for eligible employees.
• Retirement savings plans, including 401(k) in the U.S.
• Life and disability insurance.
• Employee assistance programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior