Remote Friendly (US / CA). As long as you are located in the Pacific or Mountain time zones, you are welcome to work from where you love to live and still be a key part of Lime!
Lime is the global leader in micro-mobility, with operations in 80 cities across 4 continents. With our electric bikes and scooters, we aim to revolutionize urban mobility by offering clean, efficient, and affordable transportation options to city residents.
Data is at the core of every decision at Lime – from designing vehicles, to deploying them, enhancing the user’s experience, optimizing our supply chain or warehouse operations. Every team at Lime engages with Data Science & Analytics. Our goal is to provide data insights and models that drive better business outcomes.
We are looking for intellectually curious, highly motivated individuals to join our Data Science & Analytics team. You will partner with our Engineering, Product, and Operations teams to identify critical issues to the business, develop a deep understanding of them, and design scalable solutions. You will leverage your quantitative and modeling skills to transform signals into insights, and insights into actions. You should have strong analytical skills, excellent communication abilities, and a knack for working across teams in a fast-paced environment.
What you’ll do
- Develop a deep understanding of a particular problem space that’s relevant to the business and propose solutions to improve it
- Conduct statistical analysis to extract insights from the data and communicate findings
- Guide product and strategic decisions with experimentation and in-depth analyses
- Build models that help optimize business decisions
- Develop solutions that make data insights accessible to all
- MS or PhD in Economics, Statistics, Applied Mathematics, or other quantitative fields
- 5+ years of industry experience as a Data Scientist
- Proficient in SQL and a programming language such as Python
- Hands-on experience with data pipelines and visualization tools
- Deep and practical understanding of probability and statistics, including causal inference
- Solid understanding of Machine Learning algorithms – practical experience building ML models preferred
- Ability to communicate technical concepts to a general audience
- Great product intuition and ability to generate hypotheses alone
- Capable of turning insights into actionable product ideas
- Strong communication skills with a consistent record of collaborating across a wide variety of teams and disciplines in a dynamic environment