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

8 years

0 Lacs

Posted:3 days ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Full Time

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

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