About this opportunity
Compunnel, Inc. lists this Senior Data Scientist GenAI / RAG opportunity in houston, Texas. Review the employer’s description below for duties, qualifications and application requirements.
Job description
We are seeking a Senior Data Scientist with a strong background in traditional Machine Learning, Deep Learning, and hands‑on experience building enterprise Generative AI solutions. This role is responsible for developing and deploying AI-powered applications, Retrieval-Augmented Generation (RAG) systems, predictive models, and data-driven solutions that solve complex business problems. The ideal candidate will collaborate with cross-functional teams, interact directly with customers, and leverage modern AI technologies to deliver scalable enterprise solutions.
Key Responsibilities
Build, deploy, and optimize Retrieval-Augmented Generation (RAG) systems and AI-powered chat interfaces.
Develop enterprise Generative AI solutions using Large Language Models (LLMs) and related technologies.
Design, develop, and implement machine learning algorithms to solve complex business problems.
Analyze large and complex datasets to generate actionable insights and support data-driven decision-making.
Build predictive models and statistical solutions to improve enterprise products and business outcomes.
Collaborate with client data science teams across Machine Learning and Deep Learning ecosystems.
Work closely with product managers, engineers, and business stakeholders to integrate AI and data science solutions into enterprise products.
Develop and deploy machine learning models for production environments.
Perform feature engineering, data preparation, and model optimization.
Build enterprise knowledge solutions using Generative AI technologies.
Work with structured and unstructured datasets to extract meaningful insights.
Collaborate directly with customers and stakeholders to understand business requirements and recommend AI-driven solutions.
Communicate technical findings and recommendations effectively to both technical and non-technical audiences.
Mentor junior data scientists and contribute to knowledge sharing across the team.
Stay current with advancements in Machine Learning, Deep Learning, Generative AI, and data science technologies.
Support continuous improvement initiatives by evaluating emerging AI frameworks, tools, and best practices.
Required Qualifications
Overall 10+ years of professional experience in Data Science, Machine Learning, Artificial Intelligence, or related technical fields.
Strong experience in Machine Learning (ML) and Deep Learning (DL).
Hands‑on experience with Generative AI technologies, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.
Experience developing enterprise AI and machine learning solutions.
Strong proficiency in Python or R.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Strong understanding of statistical analysis, predictive modeling, and data modeling techniques.
Experience working with SQL and querying large datasets.
Familiarity with big data technologies such as Hadoop, Spark, or similar platforms.
Experience working within AWS cloud environments.
Experience working with Snowflake or similar enterprise data platforms.
Strong analytical, problem‑solving, and critical‑thinking skills.
Excellent communication, collaboration, stakeholder management, and client‑facing skills.
Ability to work effectively with cross‑functional teams in an enterprise environment.
Preferred Qualifications
Exposure to Agentic AI and Agent APIs.
Experience with Claude, Anthropic, or similar Generative AI development platforms.
Domain experience within the Oil & Gas or Energy industry.
Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
Experience working with enterprise software products.
Understanding of cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
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Worksite address
houston, TX, 77246, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.