Senior Data Scientist

This role is for a Senior Data Scientist who will develop and deploy AI-driven solutions across predictive modeling, personalization, recommender systems, optimization, and GenAI, with an emphasis on responsible AI. You will partner with business stakeholders and apply advanced AI/ML tools and platforms to support customer engagement and decision optimization use cases.

Role Responsibilities

• Develop and deploy AI-driven solutions for customer engagement, personalization, recommendation, decision optimization, and customer insights.
• Partner closely with business stakeholders and use advanced AI/ML tools and platforms to address diverse business problems.

Required Qualifications

• Master’s or Ph.D. degree in Computer Science, Data Science, Operations Research, Statistics, Applied Mathematics, or a related discipline.
• 5+ 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, predictive modeling, propensity models, recommender systems, deep learning, and graph-based learning techniques.
• Experience using 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, written, and presentation skills, with the ability to communicate effectively with both business and technical teams.
• Hands-on experience building predictive machine learning models, recommender systems, ranking models, and prescriptive optimization models.
• Proficiency in Python, SQL, MLOps, and modern AI/ML development frameworks 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 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, Transformers
• AWS Sagemaker
• LLMs, GenAI, RAG, LLM fine-tuning
• A/B testing, graph-based learning techniques

Compensation and Location

• Location: Brooklyn, NY (hybrid)
• Salary: USD 80,420 - 106,050 per year

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

Nice to Have Skills

• Experience applying ML, DL, Econometric, and Foundation Models for time series forecasting
• Experience 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

Life at Capgemini

Capgemini supports all aspects of your well-being throughout the changing stages of your life and career.