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About the Role
Lead the Experimentation & Failure team, reporting to the CITO. You'll out-experiment and out-fail the competition by running high-velocity, rigorous experiments across every show, creator, piece of content, and commercial bet at Steven.com. You will build a team and a culture that treats deliberate failure as the primary learning mechanism. This role is deeply hands-on, involving setting hypotheses, isolating variables, checking statistical power, reading results, and moving to the next test.
Responsibilities
- Own and drive the experimentation agenda across every show, creator, and IP property.
- Lead hypothesis formation for every experiment with clear success, failure, and inconclusive criteria defined in advance.
- Enforce single-variable discipline across all experiments.
- Ensure every experiment is adequately powered before launch, including sample size calculations and defined measurement windows.
- Systematically increase experimentation velocity and build the intake process for high-volume testing.
- Build institutional memory by creating a searchable, structured record of every experiment run, its learnings, and decisions.
- Partner with the VP of Engineering & Applied AI to apply AI tooling to experiment design, analysis, and reporting.
- Ensure infrastructure supports testing at high velocity.
Requirements
- Deep, first-principles command of experimentation mathematics: statistical significance, power, sample size calculation, p-values, confidence intervals, Type I/II errors, and the difference between statistical and practical significance.
- Genuine mastery of the scientific method applied to product and content: hypothesis formation, single-variable isolation, measurement design, and result interpretation.
- A track record of building experimentation culture, not just running tests.
- Comfortable querying data and working shoulder-to-shoulder with engineers and data scientists at implementation depth.
- Strong written and verbal communication skills.
- Experience operating at pace in high-volume testing environments where speed of learning is the competitive edge.
- Demonstrable experience leading product or content experimentation programs at a technology, media, or creator-economy company.
- Owning the methodology, volume, and culture of experimentation programs.
- Experience with algorithmic platforms and designing experiments against platform-specific metrics.
- Experience in podcasting, video, social, or creator-economy.
- Familiarity with YouTube/Spotify/social analytics (CTR, retention, watch time, audience behaviour).
- Experience building an experimentation platform from scratch.
- Familiarity with causal inference beyond standard A/B testing (holdouts, quasi-experiments, diff-in-diff).
- Experience experimenting on AI/ML systems or prompt variations in production.
- A background in statistics, maths, CS, economics, or a natural science.
- Exposure to early-stage environments where you had to build the experimentation infrastructure yourself.
Skills
- Experimentation mathematics
- Scientific method
- Product experimentation
- Content experimentation
- Data querying
- Communication
- Algorithmic platforms
- Experiment design
- Experiment analysis
- Experiment reporting
- AI tooling
- Causal inference
- A/B testing
- AI/ML systems experimentation
- Prompt variation experimentation
Location
- London
Work Type
- Full-time
Experience Level
- Senior
- Lead
Education Level
- Statistics background
- Maths background
- Computer Science background
- Economics background
- Natural Science background
About the Company
- Steven.com is building the operating system for the creator economy.
- The creator economy is forecast to pass a trillion dollars by the early 2030's.
- Steven.com provides end-to-end Operating System solutions designed to scale what is irreplaceably human.
- The company has built proprietary technology and obsessed teams to identify and scale high-potential creators.
- Core pillars include Creator Media, Creator Community, Creator Products, and Creator Tech & Intelligence.
- The Experimentation & Failure team has a strategically important mandate to increase the rate of failure to learn faster than anyone else.