Senior Fraud Risk Analyst

Braviant Holdings

$80K — $110K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Degree in Data Science, Applied Mathematics, Statistics, Economics, Computer Science or related field
  • 4-6 years of experience in fraud, risk, or analytics in fintech or financial services
  • Strong analytical skills using SQL, Python, Excel, or similar tools
  • Understanding of fraud types, especially synthetic identity and first-party fraud
  • Experience with fraud detection strategies and identifying fraud patterns
  • Ability to translate analysis into actionable strategies and exposure to experimentation frameworks
  • Passionate about continuous skills development

Responsibilities

  • Analyze application data to identify fraud patterns effectively
  • Develop and implement fraud detection strategies and decisioning logic
  • Monitor early performance metrics to detect potential fraud losses
  • Distinguish between fraud risk and credit risk to enhance approval quality
  • Evaluate and optimize third-party fraud detection tools and data sources
  • Design and execute tests to refine fraud strategies
  • Collaborate with Product and Engineering to implement fraud rules
  • Investigate and adapt to emerging fraud trends through policy recommendations
  • Foster cross-department collaboration to align decisions with business goals

Benefits

  • Comprehensive healthcare including medical, dental, and vision coverage
  • Generous paid time off (PTO), sick leave, and 13 company holidays
  • 401(k) plan with company contributions
  • Annual discretionary bonus participation
  • Regular team and company gatherings
Full Job Description
POSITION SUMMARY

We are building and scaling a high-performance consumer lending platform and are looking for a Fraud Risk Analyst to help protect the business from identity fraud, first-party fraud, and credit abuse.

This role sits at the intersection of fraud, credit, and analytics, and will directly impact early loss performance and portfolio quality.

You will be responsible for identifying fraud patterns, building detection strategies, and implementing controls that prevent bad actors from entering the portfolio.

This is a hands-on, high-impact role suited for someone who is analytical, detail-oriented, and biased toward action, not just case review.

You will work closely with Credit, Product, Operations and Engineering to ensure fraud risk is properly identified and separated from credit risk in decisioning.

This role is Addison, TX-based with a 4-day in-office requirement.

WHAT YOU'LL BE DOING

  • Analyze application and early performance data to identify fraud patterns, including synthetic identity, first-party fraud, and credit abuse.
  • Develop and implement fraud detection strategies, including rules, thresholds, and decisioning logic.
  • Monitor early performance (e.g., FPD, zero-pay accounts) to identify potential fraud-driven losses.
  • Distinguish fraud risk vs credit risk, improving approval quality and reducing early loss.
  • Evaluate and optimize third-party fraud tools and data sources (e.g., identity verification, device intelligence, consortium data).
  • Design and execute tests to evaluate fraud strategies and improve detection performance.
  • Work with Product and Engineering to implement fraud rules and ensure accurate execution in production systems.
  • Investigate emerging fraud trends and proactively recommend changes to controls and policies.
  • Collaborate with Operations or servicing teams to improve fraud identification post-origination.
  • Collaborate cross-functionally with other departments to ensure decisions align with business goals and risk appetite.

WHAT YOU'LL BRING

Required
  • Degree in Data Science, Applied Mathematics, Statistics, Economics, Computer Science or a related field
  • 4-6 years of experience in fraud, risk, or analytics, preferably in fintech, lending, or financial services
  • Strong analytical skills with experience using SQL, Python, Excel, or similar tools to analyze large datasets
  • Understanding of key fraud types, including synthetic identity and first-party fraud and familiarity with fraud tools (i.e. identity verification, device fingerprinting, consortium data)
  • Experience identifying fraud patterns or working with fraud detection strategies (i.e. credit washing etc.)
  • Ability to translate analysis into clear actions (rules, controls, strategy changes) and exposure to A/B testing, experimentation frameworks, or champion/challenger strategies
  • Passion for keeping your skills up to date and exploring new methodologies
  • The ability to distill complex problems and analysis into a clear and concise narrative

Preferred
  • Experience in subprime consumer lending, fintech, payments, or another regulated financial services technology environment.
  • Hands-on experience applying AI to fraud management

BENEFITS & PERKS

Compensation at Braviant is competitive and commensurate with experience. Details will be discussed with qualified candidates during the interview process. In addition, we provide:
  • Comprehensive healthcare including medical, dental, and vision coverage
  • Generous paid time off, including PTO, sick time, and 13 company holidays
  • 401(k) with company contribution
  • Participation in annual discretionary bonus plan
  • Regular team and company gatherings

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