• You’ll collaborate with top-tier professionals in a fast-paced, inclusive environment, working with cutting-edge technologies like Large Language Models (LLMs), Generative AI, and Knowledge Graphs
• Your Role Develop and optimize predictive and prescriptive models to extract insights and enhance decision-making
• Apply deep learning and neural network techniques for customer classification, segmentation, and personalization
• Utilize MLOps to efficiently deploy, monitor, and maintain ML models in production
• Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for automation and user engagement
• Explore and integrate knowledge graphs to enhance data relationships and improve AI-driven recommendations
• Work with data engineers to design and develop robust data pipelines for large-scale ETL processing using SQL and cloud-based solutions (GCP preferred)
• Write complex SQL queries for extracting, transforming, and loading (ETL) data efficiently and implement CI/CD workflows to automate model training, deployment, and monitoring

Collaborate in an Agile/DevOps environment, promoting a data-centric culture and clearly communicating complex methodologies and insights to technical and non-technical audiences

• Your Skills and Experience 7+ years of experience in Data Science, Machine Learning, or related fields
• Experience with MLOps tools (MLflow, Kubeflow, Airflow) for model deployment and monitoring
• Proficiency in cloud platforms (GCP/AWS) and scalable data engineering
• Strong understanding of probability theory, statistics, and experimental design (A/B Testing)
• Experience with collaborative software engineering practices (Agile, DevOps)
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or related field
• Background in Retail and Personalization Web Technologies
• Understanding of digital ecosystems and data-driven decision-making

Proficiency in BI tools and data visualization

• Strong expertise in Python, SQL, and modern ML frameworks (TensorFlow, PyTorch, Scikit-Learn)

Hands-on experience in LLMs (e.g., GPT, BERT, LLaMA, Claude) and Generative AI technologies

• The base compensation range for this role in the posted location is: $86,900.- $168,688/YearCapgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws
• The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting
• The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction
• These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity

It is not typical for candidates to be hired at or near the top of the posted compensation range.In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws

• Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees

In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: 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 LeaveMedical, 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
• Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws