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# Senior Data Scientist

- **Company:** Zipline
- **Location:** South San Francisco, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Big Data, C++ (Programming Language), Computer Programming, Database Queries, Python (Programming Language), Machine Learning, Routing, Information Technology, Power Analysis (Cryptography), Operational Systems
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_801b7f840a50cbedd50354cd80c44a72

## About the Role

* 6+ years of experience in data science, machine learning, applied statistics, operations research, economics, or a related analytical field.
 * Experience applying machine learning, statistical modeling, optimization, or causal inference to real-world product or business problems.
 * Strong Python, C/C++, or Go programming skills, plus SQL proficiency and experience working with large, complex datasets.
 * Experience designing and interpreting experiments, including A/B tests, multiarm bandits, power analysis, metric design, and ambiguous causal results.
 * Experience with marketplace, logistics, mobility, delivery, pricing, routing, fleet management, or similarly complex operational systems.
 * Ability to build usable, explainable models and tools and to drive work from problem definition through measurable business impact.
 * A quantitative degree in computer science, statistics, mathematics, operations research, economics, engineering, physics, or a related field; advanced degree preferred, not required.

## Description

* Lead analysis and decision systems for priority domains including pricing, routing, fleet utilization, charging strategy, experimentation, and network planning.
 * Frame ambiguous business and product questions, select the right analytical approach, and make clear recommendations with tradeoffs and expected impact.
 * Build machine learning, statistical, optimization, forecasting, and simulation models for marketplace, operational, and product decisions.
 * Design and analyze A/B tests, quasi-experiments, causal studies, and metric frameworks to evaluate features, policies, and growth interventions.
 * Partner with engineers to productionize models, decision systems, data products, and experimentation infrastructure.
 * Own post-launch decision quality by monitoring model and KPI performance, identifying drift or missed outcomes, and driving iterations with engineering and operating partners.
 * Communicate complex findings to technical and non-technical stakeholders, aligning teams on decisions that improve reliability, utilization, customer experience, and unit economics.