Staff-Principal Data Scientist

Senior individual contributor role leading the design and improvement of machine learning-powered solutions in a production environment. The position focuses on complex user-facing AI systems, driving experimentation and model improvement, and collaborating with cross-functional teams to turn ambiguous problems into scalable solutions.

The role requires proven experience as a Staff Data Scientist, Applied Scientist, or ML Engineer with end-to-end ownership of ML or LLM initiatives. Candidates need strong hands-on experience with ML platforms in production, solid fundamentals in machine learning and statistics, and the ability to communicate complex technical ideas to diverse stakeholders. An advanced degree in a quantitative discipline is preferred.

Lead the development and enhancement of machine learning-based solutions for complex, real-world use cases

Translate open-ended product or user problems into clear data science approaches, experiments, and deliverable outcomes

Design, test, and refine prompts, retrieval strategies, evaluation frameworks, and model behaviors to improve quality and reliability

Build robust experimentation methods to assess model performance and compare alternative approaches

Work closely with product, engineering, analytics, and other technical teams to define priorities and drive implementation

Proven experience in a Staff Data Scientist, Applied Scientist, ML Engineer, or similar role, with strong ownership of end-to-end ML or LLM initiatives

Strong hands-on experience with machine learning platforms in production settings, including experimentation, evaluation, iteration, and quality improvement

Solid background in machine learning, statistics, and data science fundamentals

Strong coding ability and practical experience working closely with software engineering teams in production environments

Advanced degree in a relevant field such as Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related quantitative discipline is preferred