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Coframe

AI-powered experimentation platform for website optimization

Applied Scientist - Experimentation

Applied Machine LearningUpdated on Nov 10
Full-time

About the Job

Requirements

  • 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.
  • Experience modeling delayed outcomes, long-term value, proxy metrics, and incremental lift.
  • Strong software engineering fundamentals and experience building reliable production systems.
  • The ability to translate product and business problems into rigorous statistical and machine learning approaches.
  • Strong product judgment and the ability to connect technical models with customer needs and mental models.
  • Experience building personalization, ranking, recommendation, optimization, or allocation systems.
  • The ability to communicate complex technical concepts clearly to technical and non-technical stakeholders.
  • A pragmatic approach to applied research focused on solving real customer problems rather than optimizing in isolation.
  • A track record of staying current with developments in experimentation, causal inference, and decision science.

Responsibilities

  • Build experimentation frameworks that power every product line across Coframe.
  • Develop statistical models for measuring 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 that maximize conversion, engagement, revenue, and other customer outcomes.
  • Develop simulation and evaluation frameworks for experimentation and online decision systems.
  • Build analytics pipelines that transform large-scale behavioral data into actionable insights.
  • Develop causal inference and measurement frameworks for noisy, delayed, and incomplete feedback.
  • Model long-term value, proxy metrics, and delayed rewards.
  • Identify opportunities for automated performance gains across customer programs.
  • Analyze existing systems and translate findings into measurable product improvements.
  • Build a unified optimization system that operates across multiple Coframe product lines.
  • Work closely with engineering, product, and customer-facing teams to ensure statistical methods reflect real-world requirements.

About the Company

Coframe

AI-powered experimentation platform for website optimization

Coframe builds an AI-powered platform that plugs into a company’s website or ad campaigns and uses a team of AI agents to ideate, build, launch, and analyze experiments that personalize experiences. It runs on Coframe’s proprietary user-behavior model, with experiments feeding back to improve future tests, and offers AI conversion optimization, AI-generated landing pages, ad-to-landing-page optimization, and AEO/SEO tools. Unlike single-method CRO tools, Coframe coordinates multiple AI agents across strategy, design, engineering, QA, and analytics within one platform, and collaborates with partners like OpenAI to enhance UI code and ads. Its goal is to let growth teams rapidly boost conversions and revenue by turning continuous experimentation into a scalable, automated process.

Company size
51-200
Company stage
Series A
Total funding
$34.3M
Headquarters
San Francisco, CA
Founded
2023

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