Senior Data Scientist, AI Strategy

Position Overview

We are seeking an experienced Senior Data Scientist to lead the methodology, experimentation, and evaluation strategy for enterprise AI and Generative AI use cases. This role focuses on defining the right technical approach, establishing measurable success criteria, and validating solutions before they move into implementation and production.

The ideal candidate will have strong hands-on expertise in traditional machine learning, LLM evaluation, agentic AI, statistical analysis, and experimental design. The Senior Data Scientist will own the data science workstream from initial use-case scoping through proof-of-concept validation, working independently with business stakeholders and engineering teams across multiple initiatives.

This is primarily a strategy, methodology, and technical ownership role rather than a pure implementation position. The successful candidate must be able to define executable solution designs, make evidence-based recommendations, and ensure that the resulting solutions can be reliably implemented and maintained in production.

Key Responsibilities

Use Case Definition and Solution Strategy

• Translate business requirements into well-defined AI and GenAI use cases, including classification, extraction, summarization, RAG, and recommendation.
• Determine whether a problem is best addressed through traditional machine learning, an LLM-based solution, or an agentic workflow.
• Define the scope, methodology, assumptions, and technical approach for each use case.

Required Qualifications

• At least 7 years of hands-on data science experience, including ownership of methodology design for complex AI projects from scoping through delivery.
• Proven experience evaluating LLMs and agentic AI systems in addition to traditional machine learning models.
• Experience building ground-truth evaluation datasets and measuring routing correctness, tool-call correctness, groundedness, faithfulness, completeness, hallucination rates, and end-to-end task success.

Preferred Qualifications

• Experience in energy, power generation, manufacturing, or other industrial environments.
• Experience working with sensor, time-series, predictive maintenance, or operational data.
• Master’s degree or PhD in Data Science, Statistics, Applied Mathematics, or a related quantitative field.