Lime is the largest global shared micromobility business, operating in close to 30 countries across five continents. We’re on a mission to build a future where transportation is shared, affordable and carbon-free. Our electric bikes and scooters have powered more than one billion rides in cities around the world. Named a 2025 Time 100 Most Influential Company, Lime continues to set the pace for shared micromobility globally, spurring a new generation of clean alternatives to car ownership. 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. U.S. Based Position - What We Offer Comprehensive Health & Wellness: A choice of medical, dental, and vision plans. We also provide company-paid life and disability insurance and company-funded mental health benefits. Financial & Retirement Planning: 401(k) plan with both pre-tax and Roth options, and access to a Health Savings Account (HSA) with a monthly company contribution. Family & Fertility Support: Paid parental leave for birthing and non-birthing parents, plus fertility and family-forming benefits. Paid Time Off: Unlimited vacation, paid leaves, and 10 company holidays. Unique Lime Perks: Complimentary use of Lime vehicles in participating cities, a monthly phone allowance, dedicated learning and development days, and access to perks including One Medical, Wellhub, and Headspace. The salary range listed reflects what Lime reasonably expects to offer for this role, with the final base salary determined by factors such as the candidate’s location and relevant skills and experience. Depending on the position, the total compensation package may also include discretionary annual performance bonus opportunities and equity, subject to applicable plan terms and eligibility requirements.

• Conduct data science research to push our experimental methodologies to the bleeding edge of social science • Develop robust tools to uncover insights in experimental data • Prototype data science improvements to core platform features • Communicate the results of data science investigations to both internal and external stakeholders

• Develop and program methods, processes, and systems to consolidate and analyze diverse data sets to generate insights and solutions for customer solutions and program enhancement. • Identify and interpret insights from data sources and communicate findings to management. • Mine, model, and analyze large datasets utilizing descriptive, predictive, and prescriptive analytics. • Develop insights from historical loan performance data, identify swap-in opportunities to underwrite new customer populations, and develop credit solutions for customer base using various analytical techniques. • Develop and support custom score models for underwriting, pricing, and profitability. • Forecast performance of marketing campaigns and track actual performance against target. • Design and deploy model monitoring frameworks to assess the performance of partner underwriting portfolios, new product launches, and existing customer portfolios. • Advise senior management of emerging trends and risks. • Collaborate with vendors and technology teams to ensure new strategies and models are implemented accurately and as designed. • Conduct other ad hoc analyses as required to support team goals. • Other duties as assigned.

• Work with Data Scientists and Product partners to break down business questions into measurable problems. • Explore product and transactional data to identify trends, behaviors, and opportunities. • Define, calculate, and monitor key metrics that track product performance and customer outcomes. • Build dashboards, visualizations, and written summaries that clearly communicate insights. • Support experiment analysis (A/B tests), cohort analysis, segmentation, and statistical modeling. • Contribute to projects that directly inform product strategy and business decisions. • Gain exposure to how production data models and pipelines are built in a high-growth fintech environment.