Job Description
We are on the lookout for a Senior Manager, Data Analytics (Fraud Prevention) to join the Fintech team on our journey to always deliver amazing experiences.
Be part of building the financial backbone of Delivery Hero. You’ll develop products that empower millions of customers and merchants, from seamless payments to innovative financial solutions like wallets and credit. Your work will support our path to profitability by creating financial flexibility for users and enabling smooth transactions across 70+ countries.
In this role you will:
1. Lead the strategy, development, and execution of a high-performing team of data analysts, driving a deeper understanding of payments, refunds, and incentives amounting to billions of euros
2. Partner closely with AntiFraud Business, Product, and Tech stakeholders to understand the analytical needs of Risk Domain and set the roadmap for analytics work
3. Guide deep data analysis and the development of data products that drive meaningful business impact and enable data-informed decision-making
4. Collaborate closely with the Data Science team to support the development and evaluation of fraud prevention models and creative data solutions
5. Advocate for experiment-driven decision making, set up sophisticated AB tests, and use the results to drive better fraud prevention strategies
6. Engage with senior leadership and key stakeholders to communicate the insights in written and verbal form
Qualifications
What you need to be successful
7. You have experience leading data analytics teams and delivering measurable impact on improving understanding of fraud patterns and efficiency of fraud prevention tools
8. You can lead strategic and tactical planning to balance priorities of the business, internal clients, and the team
9. You have a strong background in fraud prevention and know how to strike the balance: keeping fraudsters out while making sure legitimate customers have the best experience
10. You understand deeply how to run AB tests to continuously improve fraud prevention strategies through statistical hypothesis testing
11. You can create processes and collaborate with teams to make sure the team enters a virtuous cycle of improvements
12. You have proven experience with daily practice of SQL, Python, and visualization tools such as Tableau, and Looker
Nice To Have:
13. Experience with BigQuery and Airflow
14. Good understanding of machine learning training and inference lifecycle including automated retraining pipelines