Note: The job is a remote job and is open to candidates in USA. Edison Smart® is scaling a rapidly growing experimentation program and is seeking a Senior Data Scientist to serve as the statistical brain behind it. The role involves designing, validating, and continuously improving statistical frameworks for experiments, ensuring their trustworthiness and correct interpretation.
Responsibilities
- Guardrail metrics & SRM detection: design and maintain automated anomaly detection for live experiments, including Sample Ratio Mismatch checks and traffic split validation; define alerting thresholds and circuit-breaking criteria so compromised experiments get flagged or stopped before polluting decisions; define and validate guardrail metrics for sensitivity, directionality, and interpretability
- Variance reduction & sensitivity: implement and iterate on CUPED and related pre-experiment covariate adjustment methods; develop techniques to strip noise from user historical behaviour, enabling faster detection of true treatment effects in limited-traffic or high-priority scenarios (target: shortening average experiment duration from 14 days to 9, unlocking 40%+ more experiments per quarter)
- Continuous A/A monitoring: design and run always-on A/A experiments as a health check on the data pipeline, from client-side event reporting through message queues to the real-time data warehouse; define what 'healthy' looks like for metric baseline volatility and pipeline stability
- Partner with product, engineering, and growth teams on experiment design — sample size calculations, metric selection, duration estimation, result interpretation — and advise on causal inference methods (DID, synthetic control, RDD) when randomisation isn't feasible
- Translate methods into specifications, validation scripts, and decision frameworks the team can self-serve against while maintaining rigour
Skills
- MS or PhD in Statistics, Biostatistics, Economics/Econometrics, Computer Science, or a related quantitative field
- 3+ years designing and analysing online controlled experiments at a tech company with meaningful user scale — not exclusively survey experiments or clinical trials
- Solid foundations in hypothesis testing, power analysis, multiple testing correction, and sequential testing; hands-on with at least two of: variance reduction (CUPED or similar), SRM detection, or continuous data quality monitoring
- Proficient in Python (scipy, statsmodels or equivalent) and complex SQL (window functions, CTEs)
- Strong 'AI sense' — extensive hands-on use of AI coding tools (Claude Code, OpenClaw, or similar) as a daily productivity multiplier, not a novelty
- Able to explain complex statistical concepts to non-technical stakeholders and write specifications engineers can implement directly
- Fluent in English and Mandarin, able to bridge the US R&D center with Asia-Pacific engineering and product teams in Singapore, Dubai, and beyond (comfortable with occasional early-morning/evening cross-timezone meetings)
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