Data Scientist 6 - Experimentation Platform
New
J
JobgetherData Science
Based in United StatesFull-TimeStaff
Salary$491,000–$775,000
Apply NowOpens the employer's application page
Job Details
- Experience
- 8+ years of experience applying statistics and causal inference to experimentation; 5+ years of experience working with data science programming languages
- Required Skills
- PythonSQLData science
Requirements
- Advanced degree (PhD or Master's) in Computer Science, Statistics, Economics, Applied Mathematics, or a related quantitative discipline.
- 8+ years of experience applying statistics and causal inference to experimentation, including large-scale experiment design and failure diagnostics.
- Proven experience establishing standards or developing tools adopted across multiple teams or an entire organization.
- Deep practical understanding of experimentation risks, such as sample ratio mismatches, winner's curse, regression to the mean, and false discovery rates.
- Experience converting complex data science problems into a clear, sequenced product roadmap.
- 5+ years of experience with data science programming languages, ideally Python and SQL.
- Ability to collaborate closely with engineers on APIs, schemas, and system architecture.
- Exceptional communication and stakeholder-management skills for both technical and non-technical audiences.
- Strong product sense, strategic thinking, and ability to operate effectively in an experimentation-focused environment.
Responsibilities
- Define and influence the strategic direction of the experimentation platform, including user experience, workflows, metrics, and reporting capabilities.
- Establish and continuously improve standards for experimentation and causal inference, including methods for peeking, covariate adjustment, and any-time-valid statistics.
- Ensure experiment logging, data processing, and inference methods are trustworthy, statistically sound, and verifiable through automated processes.
- Serve as a strategic partner to data science and engineering teams, translating analytical needs into scalable platform capabilities.
- Drive the consolidation of fragmented and bespoke experimentation systems into a coherent, modern, and scalable platform.
- Translate ambiguous experimentation challenges into a prioritized product roadmap for self-service tools and platform features.
- Mentor colleagues and represent the platform's methodology in organization-wide discussions.
View Full Description & ApplyYou'll be redirected to the employer's site
