Associate Data Scientist, Fraud Strategy
About The Position
The Fraud and Data Science team uses internal and external data to detect, prevent, and mitigate fraud across Happen Bank. The Associate Data Scientist turns complex data into actionable insights, develops analytical solutions to strengthen fraud strategies, and partners across Fraud, Risk, Product, Technology, and Operations while building technical and business expertise. The role is based in San Francisco and follows a hybrid work model, with in-office attendance on Tuesdays, Wednesdays, and Thursdays; remote placement is not considered. Work is primarily during local Pacific Time hours, with flexibility across time zones when necessary. Travel to Happen Bank offices or other locations may be required as needed.
Requirements
- At least 2 years of experience in data science, fraud analytics, decision science, or a related analytical role.
- Bachelor's degree or higher, or an equivalent combination of education and experience.
- Hands-on experience using SQL and a statistical programming language such as Python to work with large datasets and produce reproducible analysis.
- Working knowledge of statistical analysis, data visualization, and model or strategy performance measurement.
- Ability to translate analytical findings into clear recommendations for technical and business audiences.
- Ownership of assigned work, thoughtful questioning, and willingness to incorporate feedback to improve quality and outcomes.
- Sound judgment when handling sensitive data and applying new methods, balancing speed with accuracy, explainability, and risk.
- Practical familiarity with AI tools, an understanding of their strengths and limitations, and judgment in applying them to real-world analytical problems.
- Ability to collaborate with humility, adapt to changing priorities, and bring curiosity, integrity, and a problem-solving mindset.
Nice To Haves
- Experience in fraud, credit risk, financial services, e-commerce, or another high-volume digital environment.
- Experience with Tableau or another business intelligence and visualization platform.
- Exposure to feature engineering, predictive modeling, model monitoring, or experimentation.
Responsibilities
- Analyze large, complex datasets using SQL and Python to identify fraud patterns, emerging risks, and opportunities to improve decision-making.
- Support the development and implementation of fraud detection strategies, rules, and models based on data analysis and business requirements.
- Monitor fraud trends, loss metrics, strategy performance, and key indicators; investigate anomalies and translate findings into actionable insights.
- Build and maintain reliable queries, dashboards, and reporting in accordance with established data and business intelligence standards.
- Evaluate new internal and external data sources, features, and analytical techniques for predictive value, data quality, and practical application.
- Develop repeatable processes to monitor model and strategy performance, data accuracy, and changes in population behavior.
- Partner with cross-functional teams to translate business questions into analytical approaches and support solutions from analysis through implementation.
- Use AI-assisted tools where appropriate to accelerate exploration, coding, and documentation while validating outputs and protecting sensitive data.
Benefits
- Medical, dental, and vision plans for employees and their families.
- 401(k) match.
- Health and wellness programs.
- Flexible time-off policies for salaried employees.
- Up to 16 weeks of paid parental leave.
- Potential eligibility for long-term equity awards and an annual bonus.
- Relocation assistance, based on actual job level.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
