Capgemini

Senior Data Scientist

San Francisco, CA
✓ Verified live on the employer's own system · added 15 days ago
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Senior · 7+ yrs exp

Requirements

Education: Bachelor's degree or related field

Experience: 7+ years

What this role involves

ScikitData ScienceDatabricksMachine LearningRegressionPredictive

Skills & tools

Machine LearningSalesTroubleshootingRecordkeepingCloud PlatformsDatabricksDevopsSQL
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Full job 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

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

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.

The base compensation range for this role in the posted location is 150,000- 210,000

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This posting was published by Capgemini on their own careers system and is shown here with a direct link to apply there. Employers: for corrections or removal, contact jobs@veritahire.com.