Staff Fraud Strategy Analyst
SoFi
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Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The Role
The Staff Fraud Strategy Analyst will be a key member of the Fraud Prevention team focusing on the Banking Product. This team member will bring strong data analysis skills to help SoFi optimize our data driven fraud prevention decisions and strategies.
By joining SoFi, you'll become part of a forward-thinking company that is transforming financial services for the better. We offer the excitement of a rapidly growing startup with the stability of an industry leading leadership team.
What you’ll do:
The Staff Fraud Strategy Analyst will help SoFi develop better data driven fraud decisioning by:
- Aggregating and synthesizing data sets from multiple data environments
- Analyzing complex datasets to understand aggregate performance of fraud decisioning and granular performance of multiple decision methods
- Develop new data driven rules that optimize decisioning performance between Member experience and fraud prevention
- Work with external fraud prevention vendors to optimize their performance
- Work with business teams, operations, and product teams to implement new fraud prevention oriented features
What you’ll need:
- The Staff Fraud Strategy Analyst will be someone who is highly motivated and drive change, eager to learn, and able to work collaboratively in a complex and fluid environment.
- The ideal candidate will have strong expertise in analyzing large datasets using SQL/Python/R and other statistical analysis packages to drive strategies to balance Member experiences and loss prevention.
- Having prior experiences in financial fraud space and a minimum of 5 years experience in the financial industry