Job description

ABOUT COFRAME At Coframe, we are building a future where user and agent interfaces can adapt, evolve, and personalize themselves. We are generating revenue, growing rapidly, and trusted by companies you definitely know. Coframe is a primarily in-person company based in San Francisco, well-capitalized with backing from Khosla Ventures, Nat Friedman, the founder of Android, and others. 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. ABOUT THE ROLE: 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 WHY COFRAME Elite Team: Our founder is a serial entrepreneur who previously co-founded a $2B+ unicorn with Tom Brady and guest lectures AI at Stanford. Our team includes researchers from top institutions who created some of the world's most popular open-source code generation projects. OpenAI: We’re the only marketing technology company officially partnered with OpenAI. Our engineers and researchers work directly with their team to co-train a model specifically for our use case, which is a differentiator, and a testament to the technical caliber of our team. Inbound Leads: We’re currently growing at 120% QoQ with a consistent flood of inbound demand. We’re looking for the right saleshumans to capture this demand and market opportunity. Top VCs: We’re backed by tier-1 investors including Khosla Ventures, Nat Friedman (former GitHub CEO), and Rich Miner (Android co-founder). Joining now means getting a seat on the rocket ship before our Series A: a once-in-a-lifetime opportunity to join in the early innings. Already Crushing It: For our first product, we built proprietary generative AI technology that enables our Agents to autonomously design, code, debug, and deploy A/B tests, Landing Pages, and Personalization experiences. We effectively 10x testing velocity, replacing agencies, legacy tools, and the need to pull in-house designers and engineers for testing. In the last 6 months, we have already driven $221.4M in incremental revenue for our customers like Dropbox, Replit, and Intuit. “You guys are insane.” - OpenAI team “Coframe makes you feel like you have a team of 100 people.” - Replit team Coframe is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by applicable federal, state, or local law.

Requirements

Must-haves

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.
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
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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningdesign systems

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Paid Time Off