Senior Data Scientist – GenAI, LLM & RAG

Position Overview

The ideal candidate will bring a solid traditional data science foundation paired with hands-on GenAI experience (LLMs, RAG and agentic workflows). This role requires practical delivery capabilities and confidence when engaging with customers, not just theoretical knowledge. You will join the client’s Enterprise Products and AI practice to create GenAI and RAG-based solutions for Oil & Gas and Energy sector customers.

Responsibilities

• Build and deploy Retrieval-Augmented Generation systems and AI chat interfaces.
• Collaborate with client data science teams within ML/DL ecosystems.
• Develop enterprise knowledge solutions grounded in GenAI.
• Engage directly with stakeholders and customers to translate needs into solutions.
• Design and implement machine learning algorithms to address complex business problems.
• Analyze large datasets to derive insights informing decision-making.
• Work with product managers and engineers to integrate data science solutions into enterprise products.
• Effectively communicate findings and recommendations to technical and non-technical audiences.
• Keep abreast of advancements in data science and machine learning technologies.

Requirements

• Proficiency in Machine Learning and Deep Learning.
• Experience with Generative AI, LLMs, and RAG systems.
• Claude/Anthropic-based development or similar GenAI tools.
• Strong communication and client-facing capabilities.
• Experience with ML algorithms and statistical modeling techniques.
• Proficiency in Python or R and data manipulation libraries.
• Experience with big data technologies such as Hadoop or Spark.
• Excellent analytical skills with the ability to convey complex findings to non-technical stakeholders.
• A degree in a quantitative field such as Computer Science, Statistics, Mathematics, or related disciplines.

Technologies

• Python, R
• TensorFlow, PyTorch, Scikit-learn
• Tableau, Power BI
• Hadoop, Spark
• SQL, AWS, Azure, Google Cloud
• Snowflake
• Claude, Anthropic, LLMs, RAG, GenAI

About the Client

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

Industry Preference

• Experience in the Oil & Energy sector is highly preferred.
• Relevant companies include Halliburton, Mu Sigma, Mindtree.

Interview Process

• Three rounds of internal technical interviews.
• One mandatory face-to-face interview.
• No client round at this time.

Good to Have

• Basic exposure to Agentic AI and Agent APIs.
• Domain experience in the Oil & Energy sector.

Technical Environment

• AWS ecosystem
• Snowflake data platform

Skills and Tools Required

• Strong programming in Python or R
• Experience with TensorFlow, PyTorch, Scikit-learn
• Solid statistical analysis and data modeling knowledge
• Data visualization proficiency (Tableau, Power BI)
• Familiarity with Hadoop, Spark
• SQL and working with large datasets
• Strong problem-solving and communication skills

Preferred Qualifications

• Master’s or PhD in Computer Science, Statistics, Mathematics, or related field
• Experience in technology industry or enterprise software products
• Understanding of cloud platforms (AWS, Azure, Google Cloud)

Roles & Responsibilities

• As a Senior Data Scientist in Enterprise Products, you will apply advanced analytics to extract insights from large datasets, build predictive models, and support data-driven decision making.
• Collaborate with cross-functional teams to identify opportunities for leveraging data to enhance products and services.
• Provide mentorship to junior data scientists and foster a collaborative, knowledge-sharing culture.