Data Scientist

Job Description

(AI/ML Engineer / GenAI Engineer / Data Scientist)

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Houston TX

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Overview

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Capgemini is seeking an enthusiastic and driven Junior AI-Native Consultant to join our dynamic Energy & Utilities sector team. This role is designed for emerging talent passionate about leveraging Artificial Intelligence to solve complex industry challenges. You will contribute to innovative projects, applying advanced AI/ML techniques to optimize operations, enhance decision-making, and drive digital transformation for our clients.

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We are looking for individuals who possess a strong foundational understanding of AI concepts and have a minimum of 15 months of professional experience within the Oracle Field Service Cloud (OFSC), Oil & Gas, or broader Utilities domain. This is a client-facing role that requires excellent communication and problem-solving skills.

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Key Responsibilities

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• Collaborate with senior consultants and client teams to identify business challenges and opportunities for AI-driven solutions in the Energy & Utilities sector.

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• Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions.

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• Support data collection, cleaning, and preprocessing activities for AI initiatives.

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• Work with leading cloud technologies (Azure, AWS, GCP) and their AI/ML services.

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• Utilize platforms such as Databricks, PySpark, and modern AI frameworks.

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• Develop agentic AI workflows and intelligent agents to automate tasks and improve operational efficiency.

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• Participate in client workshops and presentations, effectively articulating technical concepts to diverse stakeholders.

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• Contribute to project documentation, reports, and client deliverables.

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• Develop reusable assets, demos, and solution accelerators.

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• Stay current with emerging AI technologies and industry trends, particularly within the Energy & Utilities landscape.

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• Foster a collaborative environment, actively sharing knowledge and best practices within the team.

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Required Qualifications

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• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field.

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• Minimum of 15 months of professional (non-internship) work experience in data science, AI, or machine learning roles.

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• Demonstrable background in the Energy & Utilities sector.

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• Foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts.

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• Proficiency in at least one AI-centric programming language (e.g., Python).

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• Experience with:

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• Generative AI concepts (GPT, Claude, LLMs)

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• MLOps, model deployment, and monitoring

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• LangChain and Retrieval-Augmented Generation (RAG) concepts

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• REST APIs, JSON, Authentication, and Integration patterns

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• Deployment tools (Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy)

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• Data engineering principles, including SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis)

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• Strong analytical, problem-solving, and critical thinking skills.

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• Excellent communication, presentation, and interpersonal skills, with proven ability to engage effectively in client-facing situations.

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• Ability to quickly adapt to new technologies and thrive in a fast-paced, evolving environment.

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Preferred Qualifications

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• Prior experience specifically with OFSC (Oracle Field Service Cloud), or general Oil & Gas industry knowledge.

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• Familiarity with industry-specific tools such as Seeq and historians (e.g., PHD).

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• Experience with any of the following:

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• data visualization tools and techniques

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• Machine Learning frameworks (TensorFlow, PyTorch, scikit-learn)

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• NLP

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• computer vision

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• graph database technology (Neo4J, Ontotext, etc.)

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• JIRA / Confluence

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• Prior project or internship experience in a consulting environment.

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