Senior Data Scientist
CapgeminiAbout the role
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Your Role
We are looking for an experienced GenAI Engineer / Data Scientist with 5-7+ years of experience in AI, machine learning, and application development. The role focuses on designing, developing, deploying, and maintaining Generative AI and Predictive AI solutions that create business value and improve operational efficiency.Key Responsibilities
Design and develop AI-powered applications and APIs.
Build and deploy Generative AI (GPT, Claude, Stable Diffusion, RAG) and Predictive AI models (regression, classification, clustering).
Develop intelligent AI agents and agentic workflows for task automation.
Deploy, monitor, and optimize AI models in production environments.
Design and maintain data pipelines, data lakes, and data warehouses.
Collaborate with business and technical teams to align AI solutions with organizational goals.
Stay updated on emerging AI technologies and contribute to reusable assets, demos, and sales initiatives.
Communicate AI concepts and outcomes to both technical and non-technical stakeholders.
Required Skills and Experience
Programming: Python, SQL
APIs: REST/JSON, HTTP requests, authentication, tokens, error handling, debugging, integrations, documentation
Cloud Platforms: Azure, AWS, GCP
Big Data Tools: Databricks, PySpark
AI/ML Frameworks: LangChain, TensorFlow, PyTorch, Scikit-learn
MLOps & Deployment: Docker, Azure DevOps, AWS ECS/EKS/Fargate, CI/CD pipelines
Databases: MySQL, MongoDB, Redis
Knowledge of RAG architectures, AI agents, and multimodal AI systems
Graph databases such as Neo4j or Ontotext are a plus
Qualifications
Bachelor's degree or higher in AI, Machine Learning, Data Science, or a related field (or equivalent experience).
Hands-on experience with:
Model deployment and monitoring
MLOps practices
Managing model and data drift
Cloud-based AI solutions
Soft Skills
Strong analytical and problem-solving abilities
Excellent communication and stakeholder management skills
Ability to work effectively in cross-functional teams
Capability to explain complex AI concepts to non-technical audiences
Ideal Candidate Profile
A professional with strong expertise in Generative AI, Machine Learning, Cloud Platforms, APIs, MLOps, and Data Engineering, capable of taking AI solutions from concept to production while collaborating closely with business stakeholders to deliver measurable outcomes.
The base compensation range for this role in the posted location is 150,000- 210,000
Capgemini 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. This range may be subject to change as permitted by law.
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 Leave
- Medical, dental, and vision coverage (or pr
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