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. The company stands out for its mission-driven approach to sustainable transportation and its global scale, operating in hundreds of cities worldwide. Working at Lime offers the chance to directly impact how people move in cities while tackling complex logistics and environmental challenges.

About This Role

As Data Science Manager for Supply, you'll lead a team developing ML models to optimize Lime's vehicle fleet—from forecasting demand to positioning scooters efficiently. This role directly impacts operational costs, rider experience, and sustainability by ensuring vehicles are available where and when needed. You'll bridge data science with product, engineering, and field operations to deploy real-world solutions.

💡 A Day in the Life

A typical day might start with a stand-up with your data science team to review model performance or A/B tests on vehicle positioning. You could spend midday partnering with Operations to analyze fleet health data or with Product to design a new pricing experiment. Later, you might mentor a scientist on a forecasting project or present roadmap updates to stakeholders, balancing technical depth with strategic alignment.

🚀 Application Tools

Generate Cover Letter

AI-powered, tailored for Lime

Interview Prep

Practice questions for this role

🎯 Who Lime Is Looking For

  • Has 5+ years in data science with proven leadership experience (managing or mentoring data scientists), ideally in logistics, mobility, or operations-heavy industries
  • Holds an advanced degree (MS/PhD) in Statistics, Applied Math, CS, or Operations Research with deep expertise in forecasting, optimization, and machine learning
  • Is proficient in SQL and Python for data analysis, ML modeling, and automation, with experience deploying models into production environments
  • Thrives in cross-functional collaboration, able to translate business problems (like fleet health or labor pricing) into data-driven solutions

📝 Tips for Applying to Lime

1

Highlight specific experience with demand forecasting or optimization models in your resume—quantify impact on operational efficiency or cost savings

2

Tailor your application to Lime's supply chain context: mention relevant projects in logistics, fleet management, or dynamic pricing

3

Showcase leadership beyond management: describe how you've mentored data scientists, built roadmaps, or influenced product strategy

4

Include examples of cross-functional work with product, engineering, or operations teams to deploy data solutions

5

Demonstrate knowledge of Lime's business model: e.g., discuss challenges in vehicle repositioning or fleet health in shared mobility

✉️ What to Emphasize in Your Cover Letter

['Your leadership philosophy for managing data scientists and aligning team work with business goals', "Specific examples of forecasting or optimization projects you've led, especially in logistics or operations", "How you've partnered with non-technical teams (like Operations) to implement data-driven strategies", "Why Lime's mission and the supply chain focus resonate with your experience and career goals"]

Generate Cover Letter →

🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Lime's supply chain challenges: research how they manage vehicle distribution, charging, and maintenance in cities
  • → Recent company news on hardware innovations (e.g., new scooter models) or operational strategies
  • → Competitors in micromobility (e.g., Bird, Spin) and how Lime differentiates its technology and operations
  • → Lime's sustainability reports or initiatives to understand their environmental impact goals

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How would you design a demand forecasting model for scooters in a new city, considering weather, events, and historical data?
2 Describe a time you optimized a complex system (e.g., vehicle routing or labor pricing) using ML or operations research techniques
3 How do you prioritize projects on a data science roadmap for supply, balancing quick wins vs. long-term impact?
4 What metrics would you track to measure the success of Lime's positioning system, and how would you test improvements?
5 Tell us about a cross-functional conflict you resolved (e.g., with Engineering or Operations) while deploying a model
Practice Interview Questions →

⚠️ Common Mistakes to Avoid

  • Focusing only on technical ML skills without demonstrating leadership or business impact in supply chain contexts
  • Using generic data science examples unrelated to logistics, forecasting, or optimization—avoid generic NLP or computer vision projects
  • Neglecting to research Lime's business model, leading to vague answers about how you'd approach supply problems

📅 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:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Lime!

← Back to Job Listing Apply Now →