Data Scientist

Capgemini; Houston (TX); On-site; USD 80,000 - 110,000; Full time

Job summary

Capgemini seeks a Junior AI-Native Consultant to join its Energy & Utilities team in Houston. You’ll apply AI/ML to optimize operations, support digital transformation, and contribute to client projects across platforms and data ecosystems.

The role requires 15+ months of data science/AI experience, with a foundation in Python and familiarity with OFSC, cloud services, and modern AI frameworks. Excellent communication and problem-solving skills are essential.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, or related quantitative field.
• Minimum of 15 months of professional data science/AI/ML experience.
• Experience in Energy & Utilities sector.
• Foundational AI/ML/Deep Learning knowledge.
• Proficiency in at least one AI-centric language (e.g., Python).
• Experience with Generative AI concepts (GPT, Claude, LLMs).
• Experience with MLOps, deployment, monitoring, and CI/CD.
• Knowledge of LangChain and Retrieval-Augmented Generation (RAG).
• Experience with REST APIs, JSON, authentication, and integration patterns.
• Experience with deployment tools (Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD (CodeDeploy, CloudFormation).
• Data engineering basics including SQL/NoSQL (MySQL, MongoDB, Redis).
• Strong analytical, problem-solving, and communication skills.
• Client-facing communication and presentation abilities.
• Ability to adapt to fast-paced environments.

Responsibilities

• Collaborate with senior consultants and client teams to identify AI-driven opportunities in Energy & Utilities.
• Assist design, development, and deployment of AI/ML models including Generative AI and Predictive AI.
• Support data collection, cleaning, and preprocessing for AI initiatives.
• Work with Azure, AWS, and GCP AI/ML services.
• Utilize Databricks, PySpark, and modern AI frameworks.
• Develop agentic AI workflows and intelligent agents to automate tasks.
• Participate in client workshops and articulate technical concepts to stakeholders.
• Contribute to project documentation, reports, and client deliverables.
• Create reusable assets, demos, and solution accelerators.
• Stay updated with emerging AI technologies in Energy & Utilities.
• Foster knowledge sharing within the team.

Skills

Python

AI concepts

Machine Learning

Deep Learning

OFSC

Azure

AWS

GCP

Databricks

PySpark

Education

Bachelor's or Master's in Computer Science/Data Science/Engineering

Tools

Azure

AWS

GCP

Databricks

PySpark

LangChain

RAG

REST APIs

Docker

CI/CD

SQL

NoSQL

Job description

Houston TX

Overview

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.

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.

Key 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.

Required Qualifications

• 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.

Preferred Qualifications

• Prior experience specifically with OFSC (Oracle Field Service Cloud), or general Oil & Gas industry knowledge.
• Familiarity with industry-specific tools such as Seeq and historians (e.g., PHD).
• Experience with any of the following:
• data visualization tools and techniques
• Machine Learning frameworks (TensorFlow, PyTorch, scikit-learn)
• NLP
• graph database technology (Neo4J, Ontotext, etc.)
• JIRA / Confluence
• Prior project or internship experience in a consulting environment.