Senior Data Scientist, Rider Team
Job Description
Description
Join to apply for the Senior Data Scientist, Rider Team role at Lime
Join to apply for the Senior Data Scientist, Rider Team role at Lime
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This range is provided by Lime. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
$107,000.00/yr – $207,000.00/yr
Lime is the world’s largest shared electric vehicle company. We’re on a mission to build a future where transportation is shared, affordable and carbon-free. Our electric bikes and scooters have powered 700+ million rides in 250+ cities on 5 continents, replacing an estimated 150+ million car trips. Named a Time 100 Most Influential Company and Fast Company Brand That Matters, Lime continues to set the pace for shared micromobility globally.
As a Senior Data Scientist on Lime’s Rider DSA team, you will play a critical role in helping us understand our riders and uncover the drivers of retention. You’ll focus on experimentation, product analytics, and data deep-dives that surface actionable insights for product and business teams. Partnering with Product, Engineering, and Operations, you’ll help shape strategy on initiatives like early-funnel adoption, second-month retention, and loyalty programs—turning data into measurable impact across Lime.
What You’ll Do
- Design, run, and analyze experiments to optimize rider experience and improve retention outcomes.
- Define project goals, success metrics, and measurement frameworks to ensure clarity and alignment across initiatives.
- Deliver data-driven solutions by translating complex analyses into clear, actionable recommendations in compelling ways that influence strategy and roadmap decisions.
- Partner with Product and other teams to evaluate and refine retention-focused initiatives such as onboarding flows, memberships, and loyalty programs.
- Conduct deep-dive analyses to identify patterns, diagnose problems, and inform strategic decisions around rider engagement.
- Identify key “aha” moments that predict long-term retention and quantify their impact on rider behavior.
About You
- MS or PhD in Statistics, Economics, Computer Science, Applied Mathematics, Operations Research, or a related quantitative field.
- 5+ years of industry experience as a Data Scientist, ideally in product analytics, growth, or consumer-facing platforms.
- Deep understanding of probability and statistics, including causal inference and experimental design.
- Proficiency in SQL and Python, with end-to-end experience with data—including querying, data manipulation, aggregation, analysis, visualization , and model deployment.
- Machine Learning & Modeling: Strong understanding of predictive modeling, price elasticity estimation, and customer segmentation techniques.
- Business Acumen: Business intuition for how retention and loyalty levers impact user growth and long-term value.
- Strong communication skills with the ability to convey technical concepts to non-technical stakeholders.
If you want to make an impact, Lime is the place for you. Not sure if you meet all the qualifications? If this role excites you we encourage you to apply. Explore all opportunities on our career page.
Lime is an Equal Opportunity Employer, but that’s just the start. We believe different perspectives help us grow and achieve more. That’s why we’re dedicated to hiring and developing the most talented and globally diverse team – which includes individuals with different backgrounds, abilities, identities and experiences. Applicants who require a reasonable accommodation for any part of the application or hiring process can email for assistance.
Use of artificial intelligence or an LLM such as ChatGPT during the interview process will be grounds for rejection of your application.
Compensation Range: $107K – $207K
Seniority level
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Seniority level
Mid-Senior level
Employment type
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Employment type
Full-time
Job function
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Job function
Engineering and Information Technology
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Industries
Software Development
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Company
Lime
Location
Montreal
Country
Canada
Salary
100.000
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