About The Position

You will be a strategic partner to product, engineering, and trust and safety teams, responsible for defining evaluation frameworks, leading experiments (A/B, quasi-experiments, etc.), and turning offline and live model performance into product improvements. This role requires a strong track record in startup-style experimentation (moving quickly with scrappy but rigorous methods) and product experimentation at scale. The ideal candidate will also bring proven experience in leading and managing teams to deliver high-impact data science work.

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 a 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 Haves

  • 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.

Responsibilities

  • Lead end-to-end experimentation: hypothesis generation, metric design, experiment design (A/B, multivariate, sequential, etc.), analysis, and interpretation.
  • Build and maintain evaluation frameworks for LLMs: correctness, consistency, safety, hallucination detection, bias/fairness, etc.
  • Develop predictive models, classification/ranking systems, and heuristics to improve product features related to AI/language generation.
  • Collaborate with prompt engineers & model builders to test prompt strategies, fine-tuning, or model selection; work on failure modes/error analysis.
  • Automate experiment pipelines: dashboards, monitoring, alerting, instrumentation. Ensure data quality & measurement integrity.
  • Use causal inference / observational studies when randomized experiments are not feasible.
  • Present findings and recommendations to both technical and non-technical leadership; influence roadmap decisions.
  • Drive experimentation in startup-like environments: rapid iteration, learning from limited data, and balancing speed with rigor.
  • Shape large-scale product experimentation: define frameworks for experimentation at scale and integrate results into product strategy.
  • Lead and mentor teams of data scientists, analysts, and engineers; set best practices for experiment design and AI product evaluation.

Benefits

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Flexible Paid Time Off
  • Family Leave (Maternity, Paternity)
  • Short Term & Long Term Disability
  • Training & Development
  • Work From Home
  • Stock Option Plan
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