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Senior Data Scientist – GenAI, LLM & RAG | Oil & Gas Domain | Houston, TX | Full-Time

Tricon Solutions
Houston, TX

Quick Apply

Job Details

Permanent | Full-time
$130,000 - $140,000 an hour

Qualifications

AI models
Statistics
Customer communication
Data modeling
Data visualization software proficiency
Statistics
Direct client contact
Generative models
Big data systems
AI platforms (beyond public GPTs)
Computational framework
Business intelligence tools
Machine intelligence
Machine learning libraries
Query management
Machine learning frameworks
Data visualization projects
Generative AI
Cross-functional communication
Data analysis software

Full Job Description

Senior Data Scientist - GenAI / RAG (FTE)

Location: Houston, TX (Onsite - 5 Days/Week)
Employment Type: Full-Time (Permanent)
Compensation: Up to $140,000 per annum (Open to Negotiation)

About the Client

Our client is a leading digital engineering and technology services company delivering enterprise AI and data solutions to customers in the Oil & Gas and Energy sector. This is a full-time opportunity directly with our client and not with the end customer.

Industry Preference

Candidates with experience in the Oil & Gas / Energy sector are highly preferred.

Examples of relevant companies:

Halliburton
Mu Sigma
Mindtree

Interview Process

Three rounds of internal technical interviews.
One mandatory face-to-face interview.
No client round as of now.

Position Overview

We are looking for a Senior Data Scientist with a strong traditional Machine Learning/Data Science background and hands-on experience in GenAI (LLMs, RAGs, and Agentic workflows). The candidate should not be purely academic or junior; we need someone with practical implementation experience and the ability to interact confidently with customers. Strong communication and product-facing exposure are equally important.

The selected candidate will join our client//'s Enterprise Products and AI practice and work on GenAI and RAG-based solutions for customers in the Oil & Gas and Energy sector.

Key Responsibilities

Build and deploy RAG (Retrieval-Augmented Generation) systems and AI chat interfaces.
Work closely with client data science teams (ML/DL ecosystems).
Develop GenAI-based enterprise knowledge solutions.
Collaborate directly with stakeholders and customers.
Develop and implement machine learning algorithms to solve complex business problems.
Analyze large datasets to generate insights and inform decision-making processes.
Collaborate with product managers and engineers to integrate data science solutions into enterprise products.
Communicate findings and recommendations effectively to technical and non-technical stakeholders.
Stay current with the latest advancements in data science and machine learning technologies.

Mandatory Skills

Strong Experience In:

Machine Learning (ML)
Deep Learning (DL)

Hands-On Experience With:

Generative AI (LLMs, RAG systems)

Exposure To:

Claude/Anthropic-based development or similar GenAI tools.

Additional Requirements:

Strong communication and client-facing capabilities.

Good to Have

Basic Exposure To:

Agentic AI
Agent APIs

Domain Experience In:

Oil & Gas / Energy sector.

Technical Environment

AWS ecosystem
Snowflake (Data Platform)

Skills and Tools Required

Strong proficiency in programming languages such as Python or R.
Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
Solid understanding of statistical analysis techniques and data modeling.
Proficiency in data visualization tools (e.g., Tableau, Power BI).
Familiarity with big data technologies (e.g., Hadoop, Spark).
Ability to work with databases and query large datasets using SQL.
Strong problem-solving skills and the ability to think critically.
Excellent communication and collaboration skills.

Preferred Qualifications

Master//'s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
Experience in the technology industry or with enterprise-level software products.
Understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud).

Roles & Responsibilities

About the Role

As a Senior Data Scientist in Enterprise Products, you will utilize advanced analytical techniques to drive insights from large datasets. Your role will involve building predictive models and enhancing data-driven decision-making processes within the organization. You will collaborate with various teams to identify opportunities for leveraging data to optimize products and services.

About the Team

You will be part of a dynamic team of data scientists, analysts, and product managers dedicated to creating innovative solutions for enterprise-level clients. The team thrives on collaboration, leveraging diverse expertise to tackle complex challenges. A culture of continuous learning and knowledge sharing is fostered, allowing team members to stay up to date with the latest industry trends and technologies.

You Are Responsible For

Developing and deploying machine learning models to solve business problems.
Analyzing complex datasets to extract actionable insights that contribute to product development.
Collaborating with cross-functional teams to integrate data science solutions into existing products and services.
Providing mentorship and guidance to junior data scientists and fostering a collaborative environment.

To Succeed in This Role, You Should Have

Strong experience in machine learning algorithms and statistical modeling techniques.
Proficiency in programming languages such as Python or R, along with data manipulation libraries.
Experience with big data technologies such as Hadoop, Spark, or similar platforms.
Excellent analytical skills with the ability to communicate complex findings to non-technical stakeholders.
A degree in a quantitative field such as Computer Science, Statistics, Mathematics, or related disciplines.

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