Senior - Staff Data Scientist - Product Experimentation and Evaluation

Title: Senior/Staff Data Scientist - Product Experimentation & Evaluation (LLMs & AI)

Location: Remote IN; US

Type: Full-time

Workplace: Fully remote

Job Description:

We are looking for a senior-level Data Scientist to drive experimentation, evaluation, and AI/LLM-powered product improvements. In this role, you will act as a strategic partner to product, engineering, and trust & safety teams, responsible for defining evaluation frameworks, leading experiments (A/B tests, quasi-experiments, etc.), and translating both offline and live model performance into actionable product enhancements.

The ideal candidate will have a strong track record in startup-style experimentation—moving quickly and efficiently with rigorous methods—as well as experience conducting product experimentation at scale. Proven expertise in leading and managing teams to deliver high-impact data science outcomes is highly desirable.

Requirements

• ~8-12+ years of experience in data science / ML roles, ideally with experiment design / product analytics.
• Proven track record in both startup-style and large-scale product experimentation.
• Experience leading teams, setting strategy, and driving execution in cross-functional environments.
• Strong background with statistical methods, causal inference, and rigorous measurement.
• Experience using LLMs / NLP / AI / prompt engineering or closely related field.
• Excellent coding skills in Python (or similar), strong SQL; experience building and deploying models or analytic pipelines.
• Ability to work in cross-functional teams, translate technical results into business or product changes.
• Strong communication skills; ability to explain complex analyses to non-technical stakeholders.

Nice to have:

• Experience fine-tuning or working with multiple LLM providers / APIs.
• Experience with experiment platforms or building internal tooling for experimentation & model evaluation.
• Experience in voice / ASR or other multi-modal data.

Working Terms:

• Candidates must be flexible and work during US hours at least until 6 p.m. ET in the USA, which is essential for this role & must also have their own system/work setup for remote work.