Senior Data Scientist Job San Francisco area,California USA,IT/Tech

Zipline is building an autonomous delivery service that helps goods move quickly and reliably through the real world
As the service scales, decisions about pricing, routing, fleet utilization, charging, network planning, and customer experience must work across software, vehicles, and field operations
As a Senior Data Scientist on the Data Science & Analytics team, you will own high-leverage marketplace and operational decision problems from framing through launch and iteration
You will turn ambiguous questions into models, experiments, simulations, tools, and recommendations that product, engineering, operations, commercial, and business teams can use to scale the network
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 product ionize 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

Experience with marketplace, logistics, mobility, delivery, pricing, routing, fleet management, or similarly complex operational systems
6+ years of experience in data science, machine learning, applied statistics, operations research, economics, or a related analytical field
A quantitative degree in computer science, statistics, mathematics, operations research, economics, engineering, physics, or a related field; advanced degree preferred, not required
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
Ability to build usable, explainable models and tools and to drive work from problem definition through measurable business impact