We believe in a world where all cars are shared. Carsharing empowers people to get going in a smarter, easier way, while also having a positive impact on the environment and making cities more liveable. It’s this vision that propels us forward and inspires us to think even bigger.
Since April 2019, Drivy is now part of Getaround. Together, we’re the world's leading carsharing platform with a community of more than 5 million users sharing over 11,000 connected cars across 7 countries.
Our team is collaborative, positive, curious, and engaged. We think fast, work smart, laugh often, and are looking for like-minded people to join us in our mission to disrupt car ownership and make cities better.
Your missionYou’ll play a pivotal role working alongside the Customer Operations and Risk department to build data tools and run ad-hoc analyses that strengthen the safety of the platform for our customers with data-driven operations.You will be part of the risk squad working with product managers, software engineers, data analysts, and the safety team to optimize our fraud alerts and contribute to the development of new fraud detection tools.As part of the data team, you’ll take ownership of developing and maintaining data tools, as well as contributing to building best practices in and outside of the data team.
What you'll work on1. Your projects:Empower our claims operations team with relevant reports (turnaround time, opening service level, immobilisation time).Explore fraud patterns and set up new rules within our fraud detection engine.Analyse the performance of our fraud detection rules and suggest improvements.2. Your tasks:Work on cross functional analytics initiatives end to end.Collaborate with engineers to make sure we structure, collect and process data in an accurate and timely manner. You’ll be working with production and in-house tracking data, as well as data shared by integrated services and partners.Own your processing pipelines (SQL) and be responsible for tests and documentation.Conduct exploratory analysis: partner with relevant stakeholders to frame the business problem, deep dive into data to uncover insights, and discuss how to action them.Share your recommendations to cross functional stakeholders, using meaningful reports and visualisations.Design KPIs and monitor their performance towards our objectives.Empower the team by building ground truth data sets and evangelise data tools to your stakeholders.
Our stackSnowflake data warehouse, ELT managed with Airflow and dbt, our own Segment-like integrations, BI/visualisation tools such as Redash and Tableau, Python or R notebooks.
Who you'll be working with:You'll belong to the data team of 9 experienced and caring data enthusiasts, reporting into the Product department. You will report to BenjaminYou'll work hand-in-hand with your data peers, and have daily interactions with operations managers, safety analysts, software engineers and product managers.
What you'll bring to the table:1 year of experience (including internships) in a Data/BI position, in a tech environmentBackground in quantitative fields eg Maths, Statistics, Engineering or Business with very strong analytical skills and willingness to learn more technical skills.Strong ability to turn complex data into actionable insights in a fast-paced environmentExperience with writing SQL queries, joining large datasets from multiple sourcesInterest in product: you think about possible product improvements in your day-to-day interactions with any appProficient English levelExperience with R, Python or other data-oriented programming languages is a strong plusExperience in operations analytics or fraud prevention is a plus
What we offerGetaround Europe is a fast-growing startup located in the centre of Paris, with global headquarters in San Francisco. We offer one of the most dynamic and diverse company cultures in town, and give every employee the opportunity to grow and the power to define their impact at Getaround.This position is based in Paris, with flexible remote policy (up to 2 days of remote work per week).