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# Senior Data Scientist

- **Company:** Capgemini
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $150,000.0 - $210,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, User Authentication, Microsoft Azure, Cloud Computing, Cloud Engineering, Information Engineering, Data Warehousing, Software Debugging, Graph Database, Hypertext Transfer Protocols (HTTP), JSON, Python (Programming Language), Machine Learning, MongoDB, MySQL, Neo4j, Redis, Tensorflow, Software Engineering, SQL Databases, Systems Integration, Google Cloud, Pytorch, Large Language Models, Generative AI, AWS ECS, Build Management, Data Lakes, Pyspark, Scikit Learn, AWS Fargate, Data Management, Machine Learning Operations, Stable Diffusion, GPT, Docker, Databricks
- **Published:** July 25, 2026
- **Apply:** https://www.capgemini.com/jobs/523795-en_GB_SAPBTP/x/

## About the Role

Programming: Python, SQL, 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, 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.

## Description

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., 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


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