Senior Data Scientist Payments Fraud at Lime

Lime is the world's largest shared electric vehicle company. We are on a mission to build a future of transportation that is shared, affordable and carbon-free. Named a Time 100 Most Influential Company in 2021, Lime has powered more than 250 million electric bike and scooter rides in more than 200 cities across five continents, saving an estimated 60+ million car trips. Learn more at li.me! 



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 insights, excellent communication abilities, and a knack for working across teams in a fast-paced environment.


What You'll Do:

Collaborate with Product, Engineering, Operations and Finance to optimize the revenue loss due to fraud, abuse (promotions, referrals, refunds etc.) and carry out deeper analysis to optimize the payments process (fee, latency, payment service provider waterfall etc.)
Develop machine learning models and rules to detect fraud and abuse
Carry out deeper analysis, build dashboards to track key metrics 
Develop instrumentation to track progress against key business objectives
Design, instrument, and analyze experiments to quantify the impact of product and operation changes and  produce reliable insights that drive business efficiency
Develop production-ready code and/or partner with engineering to deploy models/rules in the production environment
Contribute to fraud and abuse related incident response
Optimize the tradeoff between fraud and abuse prevention vs good user experience



About You:

A PhD or MS in a quantitative field (e.g., Operations Research, Economics, Statistics, Sciences, Engineering)
5+ years of full-time work experience as a Data Analyst / Data Scientist at a technology or payments company
Advanced proficiency in SQL and a data manipulation language, such as R or Python
Hands-on experience with data pipelines, ETLs, and data visualization tools
Solid knowledge of statistical analysis techniques such as hypothesis testing and regression
Strong knowledge and hands-on experience on machine learning, or statistics and experimentation 
Strong communication skills with a consistent record of collaborating across a wide variety of teams and disciplines in a dynamic environment
The ability to communicate results clearly to technical and non-technical audiencesPrior knowledge/experience on payments and fraud mitigation preferred



What We Offer:

Opportunity to revolutionize transportation in cities around the world with the leader in urban mobility solutions.
Scale with a rapidly growing organization, with significant opportunity for growth.
Play a role in the transformation of urban mobility and sustainability.
Work with a team of successful, fun and motivated people.
Competitive salary and benefits.



In accordance with Colorado State Law, if the candidate selected for this job resides in Colorado, the anticipated minimum salary will be $106,000,plus bonus and equity (when eligible), as well as benefits. Exact salary will ultimately depend on the candidate’s qualifications. In addition to base salary, this role will be eligible for a variable bonus based on a combination of management discretion and employee performance.

Lime is an Equal Opportunity Employer, but that’s only the start. We strive to build a workforce composed of individuals with different backgrounds, abilities, identities, and mindsets—not just to do great work, but to become a better company and grow as individuals.