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.
We are looking for a marketing analytics or applied science leader who can utilize best-in-class experimentation techniques to optimize the performance of Lime’s lifecycle marketing campaigns, pricing, promotions, and other rider incentives for a large and rapidly growing global business. This role sits at the intersection of analytics, strategy, and execution, and it involves applying machine learning to improve the ROI of campaigns of both broad reach and very precisely targeted campaigns.
The ideal candidate will have a strong applied science background and be comfortable not only with basic lifetime value and next best action concepts, but also advanced multi-arm bandit, contextual bandit, and related reinforcement learning techniques. You will be expected to utilize, enhance, and tune campaign performance and targeting utilizing tools such as StatSig or Braze, as well as foundational models built internally by Lime’s data science team. You will also lead a small team and be expected to be both a hands-on analytical expert and a strategic partner—comfortable building models, guiding teams, and influencing senior stakeholders. High proficiency with big data, SQL, Python, and Tableau are also important. While you won’t be coding foundational models or publishing Tableau reports yourself, you will be directly managing data analysts and working closely with Lime’s central data science team who will.
This is a remote position with a requirement for candidates residing in London to maintain effective collaboration across teams.
What you'll do:
Implementing pre/post, A/B test, and multi-arm bandit experiments with statistical rigor, clear objectives, measurable outcomes, and repeatable learnings and insights
Evaluating the effectiveness of various promotion constructs and redemption constraints
Setting program-level, campaign-level, and initiative-level performance benchmarks
Supporting strategic initiatives such as new product launches, market entry, partnerships, or channel expansion
Deeply understanding the Lime customer journey and where well-structured communications or incentives can motivate the right behavior changes
Managing and mentor a small team of analysts, setting high standards for analytical quality and business impact
Acting as a trusted advisor to senior leaders, influencing decisions through data and structured thinking
Partnering cross-functionally with Product, Data Science, Marketing, Finance, and Operations teams
About you:
Bachelor’s degree in Economics, Finance, Business Analytics, Computer Science or a related quantitative field
7+ years of experience in applied science, marketing or advertising analytics, CRM, lifecycle marketing, or a related field
Strong background in quantitative analysis, statistics, and marketing attribution
Experience with multi-arm bandit, contextual bandit, and/or reinforcement learning
Ability to clearly communicate complex insights to non-technical audiences
Preferred Experience:
MBA or MS degree in Economics or Data Science or a related field
2+ years of people management experience
#LI-Remote
#LI-KJ1
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 proud to be an Equal Opportunity Employer. We believe different perspectives help us grow and achieve more. That’s why we’re dedicated to building and developing a team that reflects a wider range of backgrounds, abilities, identities, and experiences. If you require a reasonable accommodation during the application or hiring process, please email [email protected] for assistance.
