Application Guide
How to Apply for Data Science Manager, Supply
at Lime
🏢 About Lime
Lime is a micromobility leader providing shared electric scooters and bikes that reduce urban congestion and carbon emissions. Unlike traditional tech companies, Lime operates at the intersection of hardware, logistics, and real-world operations, offering the unique challenge of optimizing physical assets across dynamic city environments. Working here means directly contributing to sustainable urban transportation while solving complex data problems with tangible impact.
About This Role
As Data Science Manager for Supply at Lime, you'll lead the team responsible for optimizing where and when vehicles are deployed, how they're maintained, and how operational labor is priced. This role directly impacts Lime's operational efficiency and profitability by improving vehicle availability, reducing operational costs, and enhancing hardware performance through data-driven decisions. You'll bridge technical data science work with real-world logistics, making this both a technical leadership and business-critical position.
💡 A Day in the Life
A typical day might start with reviewing overnight model performance on vehicle positioning, then meeting with operations managers to discuss deployment strategies for high-demand areas. You'd spend midday mentoring a data scientist on optimization techniques for routing, followed by presenting A/B test results to product leadership on labor pricing experiments. The day would end with planning the next quarter's roadmap for fleet health monitoring and hardware innovation projects.
🚀 Application Tools
🎯 Who Lime Is Looking For
- Has 5+ years of data science experience with specific expertise in demand forecasting, optimization models, or operations research, plus 1+ year managing/mentoring data scientists in a production environment
- Holds an advanced degree (MS/PhD) in Statistics, Operations Research, or related field with demonstrated ability to apply academic rigor to business problems in logistics or supply chain contexts
- Has successfully led cross-functional projects involving engineering (for model deployment), operations (for implementation), and product teams (for strategy alignment)
- Can clearly articulate how their past work in optimization or forecasting translated to measurable business outcomes like cost reduction or efficiency gains
📝 Tips for Applying to Lime
Quantify your impact on operational efficiency in past roles—specifically mention metrics like forecast accuracy percentages, cost savings from optimization, or efficiency improvements from A/B tests
Highlight any experience with spatial/temporal data or logistics optimization, as Lime's supply problems involve positioning vehicles across cities and time
Demonstrate your leadership style by describing how you've mentored data scientists on technical skills while aligning their work with business objectives
Research Lime's current markets and operational challenges—be prepared to discuss how you'd approach demand forecasting for scooters in a specific city like San Francisco or Paris
Show you understand the hardware aspect by mentioning any experience with IoT data, sensor analytics, or predictive maintenance relevant to Lime's fleet health focus
✉️ What to Emphasize in Your Cover Letter
['Your experience leading data science projects that improved operational efficiency or supply chain logistics, with specific metrics', "How you've successfully mentored data scientists and built team capabilities in optimization or forecasting domains", 'Your ability to translate between technical models and business strategy, especially in collaborating with operations teams', "Why you're specifically interested in Lime's mission and how your skills address their unique supply challenges (not just generic data science)"]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Lime's current markets and expansion strategy—understand where they operate and their growth plans
- → Industry challenges in micromobility (rebalancing, maintenance, city regulations) and how data could address them
- → Lime's leadership team and recent news about their technology or operational initiatives
- → Competitors (Bird, Spin, etc.) and what differentiates Lime's approach to vehicle deployment and management
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on technical modeling skills without demonstrating business impact or cross-functional collaboration
- Generic data science experience without specific examples in optimization, forecasting, or operations/logistics contexts
- Not showing understanding of Lime's unique operational challenges—treating it like any other tech company rather than a hardware/logistics business
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!