Data Scientist
Artificial Intelligence
Automation
Big Data
Bigdata
Cloud Data Engineering
Cloud Data Platform
Cloud Platform
Cloud Platforms
Data
Data Analysis
Data Analytics
Data Engineer
Data Engineering
Data Lakehouse
Data Platform
Data Processing
Data Science
Data Science Ml
Data Warehouse
Database
Databases
Databricks
Engineering
Generative AI
Industrial Automation
Information Technology (IT)
Large Language Models
Machine Learning
Machine Learning & Ai
Machine Vision
Mechatronics
NLP
Programming Language
Programming Languages
Rag Architectures
Robotics
Spark
SQL
Job Description
Capgemini is seeking an early-career, client-facing Data Scientist for an onsite role in Houston, TX. The position focuses on applying AI, Machine Learning, and Generative AI capabilities in the Energy & Utilities sector, including RAG-based applications and agent workflows.
Role Summary
In this role, you will develop AI-powered solutions, analytics, and automation capabilities. Responsibilities include building RAG-based applications, supporting AI agent workflows, and contributing to predictive and generative modeling efforts. You will also assist with data preparation, model deployment, monitoring, and MLOps activities while engaging with clients through workshops and solution discussions.
Key Responsibilities
- Assist in developing AI/ML, Generative AI, and Predictive AI solutions.
- Build and support AI agents, agentic workflows, and RAG-based applications.
- Work with cloud platforms including AWS, Azure, and GCP.
- Support data preparation, model deployment, monitoring, and MLOps activities.
- Participate in client workshops, presentations, and solution discussions.
- Develop reusable assets, demos, and accelerators.
- Use data-oriented programming languages and visualization tools to create techniques or analytics applications that transform raw data into meaningful information.
- Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets.
- Visualize, interpret, and report data findings, including the creation of dynamic data reports (where applicable).
Required Skills & Qualifications
- Python
- AI/ML Fundamentals
- Generative AI & LLMs
- RAG Concepts
- REST APIs & JSON
- SQL & NoSQL Databases
- Cloud Technologies (AWS/Azure/GCP)
- Docker, CI/CD, Azure DevOps
- Bachelor’s or Master’s degree in AI, Data Science, Computer Science, Engineering, or a related field
Experience Requirements
- Minimum 15 months of professional experience in AI, Data Science, or Machine Learning.
- Experience or background in Energy & Utilities and/or Oil & Gas.
- Oracle Field Service Cloud (preferred)
Technologies & Tools
- AWS, Azure, GCP
- Databricks, PySpark
- LangChain
- GPT/Claude/LLMs
- REST APIs, JSON, SQL, NoSQL Databases
- Docker, CI/CD, Azure DevOps
- TensorFlow, PyTorch, scikit-learn
- NLP, Computer Vision
- Neo4j, Graph Databases
- Seeq, PHD Historians
- Jira, Confluence
Preferred Skills
- TensorFlow, PyTorch, scikit-learn
- NLP and Computer Vision
- Neo4j or Graph Databases
- Seeq, PHD Historians
- Jira & Confluence
Compensation
USD 95,342 - 105,354 per year.
Location & Work Setup
Houston, TX (onsite).
Benefits
- Paid time off based on employee grade (A-F): 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 (for example, 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
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