Sobre este puesto de Applied Scientist, Experimentation en Coframe
At Coframe, we’re building living interfaces that continuously improve themselves.
As an Applied Scientist focused on experimentation, you’ll build the intelligence that determines what to test, how to measure impact, and which experiences to ship. You’ll develop an opinionated yet flexible experimentation and analytics platform that powers decision-making across every Coframe product line.
Your work will help Coframe extract reliable signals from noisy behavioral data, measure long-term business impact, and continuously optimize customer outcomes with less human intervention.
You’re a great fit if you have:
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 and a focus 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
What you’ll do:
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
Benefits:
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
About us:
At Coframe, we are building a future where user and agent interfaces can adapt, evolve, and personalize themselves.
We are a primarily in-person company based in San Francisco.
We are well-capitalized with backing from Khosla Ventures, Nat Friedman, the founder of Android, and others.
We are generating revenue, growing rapidly, and trusted by companies you definitely know.
Our team is small and talent-dense, consisting of competitive programmers, former founders, including our founder who previously co-founded a unicorn, and AI researchers from top institutions who have created some of the most popular open-source code generation projects.
“You guys are insane.” OpenAI team
“Coframe makes you feel like you have a team of 100 people.” Replit team