Note: The job is a remote job and is open to candidates in USA. Earnest empowers ambitious professionals to make confident financial decisions and build the life they envision. The Senior Fraud Strategy Analyst will design and optimize fraud strategies, monitor portfolio performance, and develop actionable insights to enhance fraud detection capabilities.
Responsibilities
- Design, develop, and optimize fraud strategies across personal loans and student loan refinance products
- Monitor portfolio performance to identify emerging fraud trends, risks, and optimization opportunities
- Develop and deploy fraud rules and strategies using segmentation, statistical analysis, and predictive modeling techniques
- Own end-to-end fraud mitigation processes, with accountability for fraud loss reduction and performance outcomes
- Design and execute A/B tests and champion/challenger frameworks to evaluate strategy effectiveness
- Build and maintain scalable analytical frameworks using tools such as Snowflake and dbt
- Develop dashboards and reporting (e.g., Looker) to monitor KPIs such as fraud rate, approval rate, and false positives
- Generate actionable insights from structured and unstructured datasets, including limited or noisy data environments
- Partner with cross-functional teams (Product, Engineering, Risk, Operations) and external vendors to implement fraud solutions
- Leverage internal and third-party data to enhance fraud detection capabilities
- Continuously evaluate and refine strategies based on performance metrics and evolving fraud patterns
- Communicate insights, strategy performance, and model behavior clearly to stakeholders and senior leadership
- Support model development lifecycle, including design, validation, and production deployment
Skills
- Bachelor's degree in a quantitative field (e.g., Statistics, Engineering, Analytics, Economics); Master's preferred
- 4+ years of experience in fraud risk, credit risk, or customer risk management within a financial institution or fintech
- 3+ years of hands-on experience with SQL, Python, or R for data analysis and modeling
- 3+ Proven experience designing and implementing fraud strategies for unsecured lending products (e.g., personal loans)
- Strong analytical and problem-solving skills with attention to detail
- Ability to translate complex data into clear, actionable insights
- Effective communicator with experience influencing cross-functional stakeholders
- Self-starter with a high degree of ownership, curiosity, and adaptability
- Experience with machine learning models (e.g., logistic regression, tree-based models, anomaly detection)
- Familiarity with fraud typologies (e.g., synthetic identity, first-party fraud, account takeover)
- Knowledge of regulatory frameworks and risk controls (e.g., fair lending, model governance)
- Experience with experimentation frameworks and decision systems
- Exposure to modern data stack tools (e.g., dbt, Snowflake) and BI tools (e.g., Looker)
Benefits
- Health, Dental, & Vision benefits plus savings plans
- Mac computers + work-from-home stipend to set up your home office
- Monthly internet and phone reimbursement
- Employee Stock Purchase Plan
- Restricted Stock Units (RSUs)
- 401(k) plan to help you save for retirement plus a company match
- Robust tuition reimbursement program
- $1,000 travel perk on each Earnie-versary to anywhere in the world
- Competitive days of annual PTO
- Competitive parental leave
Company Overview
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