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Applied Scientist, Experimentation

coframe · Burlingame

New
🇬🇧 English
statistics causal inference machine learning experimentation design bayesian methods reinforcement learning contextual multi-armed bandits online decision systems software engineering personalization ranking recommendation optimization allocation systems

Job description

About the role

As an Applied Scientist focused on experimentation, you will create the intelligence that decides what to test, how to measure impact, and which experiences to ship. You will build a flexible experimentation and analytics platform that powers decision‑making across every Coframe product line.

Key responsibilities

  • Build experimentation frameworks that power all product lines.
  • Develop statistical models for incremental lift, confidence, and long‑term business impact.
  • Create decision engines that automatically start, stop, ramp, and optimize experiments.
  • Design systems that balance exploration and exploitation throughout the experiment lifecycle.
  • Build personalization and optimization algorithms to maximize conversion, engagement, and revenue.
  • Develop simulation and evaluation frameworks for online decision systems.
  • Construct analytics pipelines that turn large‑scale behavioral data into actionable insights.
  • Model long‑term value, proxy metrics, and delayed rewards.

Required profile

  • A strong background in statistics, causal inference, machine learning, experimentation, or a related quantitative field.
  • Experience designing, building, or significantly evolving large‑scale online experimentation platforms.
  • Deep knowledge of experimentation design, statistical methodology, and common measurement pitfalls.
  • Experience with Bayesian methods, reinforcement learning, contextual multi‑armed bandits, or online decision systems.
  • Ability to translate product and business problems into rigorous statistical and machine‑learning approaches.
  • Strong software‑engineering fundamentals and experience building reliable production systems.

Required skills

  • Statistics
  • Causal inference
  • Machine learning
  • Experimentation design
  • Bayesian methods
  • Reinforcement learning
  • Contextual multi‑armed bandits
  • Online decision systems
  • Software engineering
  • Personalization, ranking, recommendation, optimization, allocation systems

What we offer

  • Flexible (unlimited) paid time off
  • Medical, dental, and vision benefits for you and your family
  • Life insurance and disability benefits
  • 401k plan with Coframe match
  • Meals covered in‑office
  • Gym membership

Questions fréquentes

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Source : ats:ashby

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Published 5 hours ago

Expires 1 month from now

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coframe

Burlingame