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September 14, 2026

Operations Data Scientist – Strategic Operations

Mid • On-site

140,000 - 210,000 USD/yr

South San Francisco, CA

Quick Facts

Operations Data Scientist working on predictive modeling, optimization, and analytical frameworks that drive operational decision-making across a global network.

Description

As an Operations Data Scientist, you will develop the predictive models, optimization algorithms, and analytical frameworks that drive operational decision-making across the global network. You will work at the intersection of data science, operations research, logistics, and business strategy to improve network performance, forecast demand, optimize resource allocation, and identify opportunities to scale efficiently.

What You'll Do

  • Develop forecasting models for operational demand, capacity, labor requirements, inventory, and network utilization.
  • Build optimization models that improve resource allocation, staffing, maintenance planning, and operational efficiency.
  • Design and analyze experiments to evaluate operational initiatives and process changes.
  • Create predictive models that identify operational risks, bottlenecks, quality issues, and reliability trends.
  • Develop simulation models to evaluate network expansion scenarios and operational strategies.
  • Partner with Operations, Engineering, Product, Supply Chain, and Finance teams to guide strategic decisions.
  • Build production-ready analytical tools and data products used by operational teams.
  • Establish advanced operational metrics and measurement frameworks.
  • Communicate complex analytical findings to technical and non-technical stakeholders.
  • Support long-term planning through scenario analysis and decision modeling.

Requirements

  • 3–7 years of experience in Data Science, Operations Research, Analytics, Applied Statistics, Industrial Engineering, or a related field.
  • Strong proficiency in Python.
  • Advanced SQL skills.
  • Experience with machine learning, statistical modeling, forecasting, and experimentation.
  • Experience with optimization techniques such as linear programming, mixed-integer optimization, simulation, or network modeling.
  • Strong knowledge of statistical inference and experimental design.
  • Experience building analytical solutions that influence operational decisions.
  • Ability to explain complex technical concepts to business stakeholders.

Benefits

  • Starting cash range: $140,000–$210,000 (target range; final depends on experience, qualifications, skills, working location, and projected impact).
  • Equity compensation.
  • Overtime pay.
  • Discretionary annual or performance bonuses.
  • Sales incentives.
  • Medical, dental, and vision insurance.
  • Paid time off.
  • Additional benefits may be included.

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