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Data Analyst - Customer Operations and Risk
Data & Intelligence - Paris - Full-time
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.
- You will work closely with project managers in the Customer Operations and Risk department running ad-hoc analysis and building data tools to develop data-driven operational excellence.
- 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 a member of the data team, you will be responsible for building and maintaining data tools, contributing to building best practices in and outside of the data team.
What you'll work on
- 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.
Projects you'll work on:
- Explore fraud patterns and setup new rules within our fraud detection engine
- Analyse the performance of our fraud detection rules and suggest improvements.
- Empower our claims operations team with relevant reportings (turnaround time, opening service level, immobilisation time)
- Snowflake 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 Benjamin
- You'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 environment
- Background 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 environment
- Experience with writing SQL queries, joining large datasets from multiple sources
- Interest in product: you think about possible product improvements in your day-to-day interactions with any app
- Experience with R, Python or other data-oriented programming languages is a strong plus
- Experience in operations analytics or fraud prevention is a plus
- Proficient English level
What we offer
- Getaround 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).