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Senior Fraud Strategy Analyst

3 hours, 2 minutes ago
Anywhere
Full-time
Senior
Business Analyst
Data Science and Analytics
dbt Looker Machine Learning Python R Snowflake SQL
Apply Now
Puck

Puck

Puck helps great teams find great teammates through employer branding, conversations, and authentic candidate engagement, using personalized automation to enhance the candidate experience and improve hiring metrics.

Internet Software & Services
1-10
Founded 2020
View All Jobs 2

Description

  • 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 and account 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 in tools such as Looker to monitor fraud rate, approval rate, and false positives.
  • Generate actionable insights from structured and unstructured datasets, including limited or noisy data environments.
  • Partner with Product, Engineering, Risk, Operations, and external vendors to implement fraud solutions.
  • Support the model development lifecycle, including design, validation, and production deployment.

Requirements

  • Bachelor’s degree in a quantitative field such as Statistics, Engineering, Analytics, or Economics; master’s degree 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+ years of proven experience designing and implementing fraud strategies for unsecured lending products such as personal loans.
  • Experience using machine learning models such as logistic regression, tree-based models, or anomaly detection (preferred).
  • Familiarity with fraud typologies such as synthetic identity, first-party fraud, or account takeover (preferred).
  • Knowledge of regulatory frameworks and risk controls such as fair lending and model governance (preferred).
  • Experience with experimentation frameworks and decision systems (preferred).
  • Exposure to modern data stack tools such as dbt and Snowflake, and BI tools such as Looker (preferred).
  • Strong analytical and problem-solving skills with attention to detail.

Benefits

  • Competitive base salary range of $124,000 to $155,000 USD.
  • Health, dental, and vision benefits plus savings plans.
  • Mac computers and a work-from-home stipend for home office setup.
  • Monthly internet and phone reimbursement.
  • Employee Stock Purchase Plan and Restricted Stock Units (RSUs).
  • 401(k) retirement plan with company match.
  • Robust tuition reimbursement program.
  • Competitive days of annual PTO and competitive parental leave.

Interested in this position?

Apply directly on the company website

Apply Now

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