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 specializing in Payments & Fraud, you will play a pivotal role in reducing revenue leakage, safeguarding platform integrity, and optimizing the user payment experience. You will leverage data science, experimentation, and machine learning to detect and prevent fraud and abuse, streamline payment flows, and evaluate the effectiveness of risk mitigation strategies. Partnering closely with Product, Engineering, Operations, and Finance teams, you will provide the insights and tools needed to make informed decisions, balance fraud prevention with user experience, and drive business efficiency. This role combines analytical rigor with strong business acumen to deliver measurable impact across Lime’s payments ecosystem.

What You’ll Do:

• Design and evaluate strategies to reduce fraud and abuse across promotions, referrals, refunds, and payment flows.

• Develop and improve machine learning models, rules-based systems, and heuristics to detect high-risk behavior while minimizing false positives.

• Analyze experimental and observational data using A/B testing and causal inference to measure the effectiveness of interventions in payments and fraud prevention.

• Identify and quantify key friction points in the payments funnel (e.g., latency, failure rates, PSP routing), and partner with Engineering to improve reliability and speed.

• Build dashboards, reports, and self-serve tools to empower teams with visibility into fraud trends, payment performance, uncollected revenue, and risk tradeoffs.

• Collaborate on incident response and root cause analyses for fraud and abuse events, ensuring rapid mitigation and long-term prevention.

• Stay informed on evolving fraud tactics, risk mitigation techniques, and payment technologies to proactively shape Lime’s strategy.

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, with a focus on payments, fraud detection, risk mitigation, or user trust.

• 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: Strong intuition for how pricing and loyalty strategies impact revenue, customer behavior, and long-term retention.

• Strong communication skills with the ability to convey technical concepts to non-technical stakeholders.

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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 recruiting-operations@li.me for assistance.

Use of artificial intelligence or an LLM such as ChatGPT during the interview process will be grounds for rejection of your application.