Senior/Staff Data Scientist - Product Experimentation & Evaluation (LLMs & AI)
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.
- ~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.
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