Fraud Data Analyst
SoFi
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The Role
We are seeking a versatile and skilled data analyst to join our Fraud Platform team. This role involves partnering with Risk Infrastructure, Fraud Policy, Product, and Engineering teams to enhance our fraud prevention infrastructure. The ideal candidate will have a strong data background, including proficiency in SQL, Python, Snowflake, and Tableau, and must be comfortable wearing multiple hats. You’ll need to be self-motivated and capable of working independently, with a mission to iterate and develop a world-class fraud prevention platform. If you love working with data and have a passion for doing the right thing, we want to hear from you!
What you’ll do:
The Fraud Prevention Data Analyst will be responsible for the following:
- Monitor fraud patterns and identify potential risks and threats.
- Develop and maintain reports and dashboards in Tableau to provide insights and trends to management.
- Write and publish program procedures and standards.
- Continuously assess and refine fraud prevention measures to ensure effectiveness and highlight areas for improvement.
- Conduct ad hoc analysis to support ongoing fraud prevention efforts.
- Prepare documentation and reports for regulatory examinations, audits, and internal reviews, ensuring all information is accurate and timely.
- Support the development of risk assessments and controls, working closely with 2LOD and other stakeholders to identify and mitigate risks.
What you’ll need:
- 4+ years of data analysis experience preferably with focus on risk management and/or fraud prevention
- A degree in a quantitative field of study (e.g., Statistics, Finance, Economics, Math, Sciences, Engineering)
- Ability to wear multiple hats and be able to independently execute
- Mastery of SQL and a strong understanding of data relationships / relational databases, experience working with large datasets.
- Experience with working with Snowflake and Tableau.
- Exceptional writing abilities are highly desirable.
Nice to Have:
- Experience working with multiple cross-functional teams to deliver results
- Experience in banking and/or fintech industry
- Familiarity with machine learning algorithms and techniques.
- Knowledge of fraud prevention tools and techniques.