Staff Data Scientist, Causal Inference & Experimentation

Responsibilities

• Formulate the vision and set the roadmap for the Experimentation Platform in partnership with engineering, product, and data science stakeholders.
• Provide statistical expertise to ensure experimentation methodologies and frameworks are sound and aligned with best practices in causal inference and experimental design.
• Partner with engineering and product to improve the reliability, scalability, and adoption of experimentation, including modern AI/LLM tooling where it can accelerate rigor and speed.
• Lead initiatives to educate and train cross-functional teams through workshops, training sessions, and educational materials on experimentation design, statistical methodology, and causal inference.
• Empower the Data Science team to adopt more rigorous causal inference methods.
• Lead and conduct original causal inference research on high-priority questions in partnership with the wider Data Science team.
• Engage directly with experimentation customers, including data scientists, product managers, and engineers, to ensure the platform enables fast, reliable, data-driven decisions.

Requirements

• Proven experience leading experimentation platform work, including designing and validating statistical methodologies for accurate and reliable experimental results.
• PhD in a quantitative field such as Statistics, Economics, Political Science, or Psychology, or equivalent practical experience.
• 4+ years designing, implementing, and analyzing experiments or causal inference projects.
• Ability to evaluate and recommend statistical approaches that balance velocity and reliability across product launches.
• Strong communication and education skills, including explaining complex statistical and experimental design concepts to technical and non-technical audiences.
• Experience developing and delivering training programs or educational content related to experimentation, causal inference, or statistical analysis.
• Proficiency with Python, SQL, R, and/or other statistical programming languages.

Nice-to-haves

• Interest in literature reviews and translating scientific best practices across the company.
• Experience applying causal inference methods that translated into business decisions and outcomes.
• Experience autonomously leading cross-functional projects and influencing partners.
• Comfort using AI/LLM tools to accelerate causal inference workflows, automate repetitive analysis, or scale experimentation education content.
• Passion for Discord or gaming.
• Causal inference-related publications.

Compensation and Benefits

• US base salary range: $279,000–$310,000, plus equity and benefits.
• Relocation assistance may be available.