Associate Data Scientist

Houston, TX

Full-time

Onsite

Entry Level

Capgemini is seeking an enthusiastic Junior AI-Native Consultant to join its Energy & Utilities sector team. The role supports the design, development, and deployment of AI/ML solutions, including Generative AI and Predictive AI, while collaborating with clients and senior consultants to optimize operations and drive digital transformation.

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Responsibilities

Collaborate with senior consultants and client teams to identify business challenges and opportunities for AI-driven solutions in the Energy & Utilities sector
Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions
Support data collection, cleaning, and preprocessing activities for AI initiatives
Work with leading cloud technologies (Azure, AWS, GCP) and their AI/ML services
Utilize platforms such as Databricks, PySpark, and modern AI frameworks
Develop agentic AI workflows and intelligent agents to automate tasks and improve operational efficiency
Participate in client workshops and presentations, effectively articulating technical concepts to diverse stakeholders
Contribute to project documentation, reports, and client deliverables
Develop reusable assets, demos, and solution accelerators
Stay current with emerging AI technologies and industry trends, particularly within the Energy & Utilities landscape
Foster a collaborative environment, actively sharing knowledge and best practices within the team

Qualification

Required

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field
Minimum of 15 months of professional (non-internship) work experience in data science, AI, or machine learning roles
Demonstrable background in the Energy & Utilities sector
Foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts
Proficiency in at least one AI-centric programming language (e.g., Python)
Experience with:
Generative AI concepts (GPT, Claude, LLMs)
MLOps, model deployment, and monitoring
LangChain and Retrieval-Augmented Generation (RAG) concepts
REST APIs, JSON, Authentication, and Integration patterns
Deployment tools (Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy)
Data engineering principles, including SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis)
Strong analytical, problem-solving, and critical thinking skills
Excellent communication, presentation, and interpersonal skills, with proven ability to engage effectively in client-facing situations
Ability to quickly adapt to new technologies and thrive in a fast-paced, evolving environment