Staff Data Scientist – Product Analytics

This is a fully remote position, open to applicants in Saudi Arabia.

📋 Description

• Establish and implement standards for event instrumentation and tracking plans across web, mobile, and backend systems.

• Take ownership of core product funnel definitions (such as merchant onboarding, checkout, subscription conversion) and ensure they are accurately tracked, monitored, and comprehended.

• Develop and operationalize Salla’s experimentation framework, which includes:

• Guidance on experiment design (metrics, guardrails, randomization units).

• Statistical methodologies (frequentist and/or Bayesian, sequential testing when applicable).

• SRM checks, pre-experiment power analysis, and MDE calibration.

• Documentation of post-experiment synthesis and decisions.

• Guarantee reliable and reproducible reporting of experiment outcomes — including clear communication of confidence levels, practical significance, and trade-offs.

• Collaborate with Product Managers and Engineers to integrate measurement into the product development lifecycle, from PRD to post-launch review.

• Perform in-depth product analyses (retention drivers, feature adoption, user segmentation) that inform the product roadmap.

• Work alongside the Data Platform team to enhance data quality, ensure pipeline reliability, and develop self-service analytics tools for product teams.

• Mentor product analysts and cultivate a culture rooted in analytical rigor, intellectual honesty, and curiosity.

⛳️ Requirements

• Over 7 years of experience in product analytics, data science, or applied statistics within a technology company.

• Extensive hands-on experience in designing, executing, and analyzing A/B tests at scale, including awareness of common pitfalls (SRM, peeking, metric sensitivity, novelty effects).

• Strong grasp of event-tracking architectures and best practices for instrumentation (such as event taxonomies, naming conventions, schema governance).

• Proficiency in SQL and Python (pandas, scipy, statsmodels, or equivalent).

• Solid understanding of statistical concepts: hypothesis testing, confidence intervals, power analysis, multiple comparisons, and causal reasoning.

• Experience in defining and maintaining product health metrics, guardrail metrics, and north-star metrics.

• Demonstrated ability to synthesize experiment results and product data into coherent strategic narratives for product and engineering leadership.

• Exceptional communication skills, with a history of influencing product decisions through data.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health and wellness benefits.

• Opportunities for professional development and career growth.

• Flexible work hours and a supportive work environment.