Operations Data Scientist – Strategic Operations

Posted 3 Days Ago
South San Francisco, CA, USA
In-Office
140K-210K Annually
Mid level
Aerospace • Hardware • Logistics • Robotics • Software • Transportation
Zipline democratizes access to critical medical supplies through instant drone delivery.
The Role
Develop predictive, optimization, and simulation models to forecast demand, allocate resources, plan maintenance, and evaluate network expansion. Build production-ready analytics and measurement frameworks, run experiments, identify operational risks, and partner with cross-functional teams to guide strategic operational decisions and improve network performance.
Summary Generated by Built In
About Zipline

Zipline is the world’s largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world’s largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products. 

Our customers include the world’s largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we’ve built to enable seamless, reliable, global operations.

Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.

We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people’s lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.

About the Role

As an Operations Data Scientist, you will develop the predictive models, optimization algorithms, and analytical frameworks that drive operational decision-making across our 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.

This role is ideal for someone who enjoys solving real-world operational problems with advanced analytics and building models that directly influence business outcomes.

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.

Required Qualifications

  • 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.

Preferred Qualifications

  • Experience in logistics, transportation, aviation, robotics, autonomous systems, manufacturing, or supply chain operations.
  • Experience deploying models into production environments.
  • Experience with cloud data platforms and modern data stacks.
  • Familiarity with geospatial analytics and network optimization.
  • Master's or PhD in Statistics, Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or related disciplines.

Example Problems You'll Solve

  • How many technicians will be required at each site over the next 12 months?
  • What maintenance strategy minimizes downtime while controlling cost?
  • How should inventory be positioned across the network to maximize service levels?
  • Which operational variables best predict delays, failures, or quality issues?
  • Where should future sites be launched to maximize network efficiency?
  • What is the optimal staffing model for a rapidly scaling operation?

Success Metrics

  • Forecast accuracy.
  • Measurable operational cost savings.
  • Capacity utilization improvements.
  • Reduction in operational disruptions.
  • Adoption of predictive and optimization tools by operational teams.
  • Strategic decisions influenced by analytical recommendations.

What Else You Need to Know

The starting cash range for this role is $140,000-$210,000. Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compensation package for this role may also include: equity compensation; overtime pay; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more.

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, ancestry, national origin, religion or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other characteristics protected by state, federal or local law or our other policies.

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in Zipline ’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

Skills Required

  • 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
  • Experience in logistics, transportation, aviation, robotics, autonomous systems, manufacturing, or supply chain operations
  • Experience deploying models into production environments
  • Experience with cloud data platforms and modern data stacks
  • Familiarity with geospatial analytics and network optimization
  • Master's or PhD in Statistics, Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or related disciplines

Zipline Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zipline and has not been reviewed or approved by Zipline.

  • Healthcare Strength Healthcare coverage is consistently described as comprehensive and high quality, with multiple plan choices, low out‑of‑pocket costs, and additions like HRA, One Medical, and fertility support.
  • Parental & Family Support Parental and family leave is highlighted as generous and meaningfully used, reinforcing support for major life events.
  • Leave & Time Off Breadth Paid time off, sick days, and holidays are portrayed as solid and broadly available, contributing to overall benefits depth.

Zipline Insights

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The Company
HQ: South San Francisco, CA
375 Employees
Year Founded: 2014

What We Do

Zipline is the world's largest autonomous delivery network and is powered entirely by fixed-wing drones. Our fleet circles the equivalent distance of the equator every 2.5 days, and we have shipped hundreds of thousands of critical medical products across Rwanda, Ghana, and now beginning in the United States.

Why Work With Us

Zipline is the perfect intersection of super cutting-edge tech, deep social mission, and extremely compelling business case. Our small, scrappy, customer-obsessed, humble, and mission-driven team has set the bar for what is possible in the drone logistics industry globally, and has designed some incredibly elegant technology in the process.

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