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 400+ million rides in 250+ cities on 5 continents, replacing an estimated 100+ million car trips. Named a Time 100 Most Influential Company and Fast Company Brand That Matters, we achieved a fully profitable year in 2022, becoming the first in our industry to reach this milestone.

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. Doing our job well means that we enable the entire organization’s ability to make more informed decisions, innovate faster, and serve our customers better.

We are looking for an intellectually curious, highly motivated individual 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
• A highly skilled professional with expertise in product knowledge and intuition, ideally applied in consumer product development settings.
• A statistical expert with strong statistical knowledge and intuition, ideally applied in experimentation and observational causal studies settings.
• Proficient in quantitative programming languages, such as Python or R.
• Skilled in SQL and familiar with distributed data stores like S3, Presto, Hive, and Spark.
• Highly effective in engaging with diverse stakeholders and adept at cultivating strong partnerships.
• Excellent with communication, conveying technical content to non-technical audiences, and collaborating across different functions to ensure real business impact.
• Strategic-minded, impact-driven, and able to incorporate a larger business context into data questions and product development.
• Experienced in building real-world machine learning models with demonstrated impact
• Adept in Data Processing; performing essential data preprocessing tasks, applying data transformation, normalization, and feature engineering to prepare datasets for analysis.

Preferred Qualifications:

• Experience with tools like Airflow and dbt to contribute to the creation and optimization of data pipelines, aiming to automate and improve data flow within the organization.
• Prior knowledge/experience on payments and fraud mitigation

The anticipated salary range for this position is CA$ 86,000  to CA$139,000. Equity and benefits may be provided as part of the compensation package, depending on the position offered. Not all candidates will be eligible for the upper end of the salary range. Exact salary will ultimately depend on multiple factors, which may include the successful candidate’s skills, experience and other qualifications as well as the candidate’s location of residence. In addition to base salary, some roles may be eligible for a variable bonus based on a combination of company performance, employee performance, and management discretion.