Senior Fraud Risk Analyst

United StatesUnited States·DallasFull Timesenior
Risk AnalystData & AI
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Quick Summary

Overview

At Braviant, we believe in hiring great talent and offering them the flexibility to achieve great results unbounded by geography. Braviant is offering a fully remote option for anyone in the U.S. who wants to join our team and help us grow.

Technical Tools
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Title: Senior Data Scientist
Function: Credit Risk
Reports to: Head of Credit
Level: Mid-Level / Senior
Location: Addison, TX (5 days/week in-office)

Please note: This position is open to candidates within commuting distance to the DFW metro area only. Applicants must reside in Texas and be authorized to work in the United States. Applications from candidates outside of Texas will not be considered at this time. While we appreciate interest from all applicants, Braviant Holdings is unable to sponsor visas at this time.

Founded in 2015 and based in Chicago, IL, privately held Braviant Holdings, LLC is a leading provider of tech-enabled consumer credit products that combine breakthrough technology and cutting-edge machine learning to transform how people access credit online. Our next-generation approach to lending reduces credit barriers and creates a Path to Prime® — helping millions of underbanked consumers build credit history, reduce their cost of borrowing, and take control of their personal finances. Braviant has been named multiple times to the Inc. 5000 list of fastest growing private companies and has been recognized as a Best Place to Work.

We are a lean team of approximately 40 people who move fast and hold ourselves accountable for real outcomes. Everyone here rolls up their sleeves — including this role.

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.
  • 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.
  • 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
  •  

    Nice to Have

    ~1 min read
  • Experience in subprime consumer lending, fintech, payments, or another regulated financial services technology environment.
  • Hands-on experience applying AI to fraud management
  • 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
  • Braviant is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, or any other characteristic protected by applicable law.

    Location & Eligibility

    Where is the job
    Dallas, United States
    On-site at the office
    Who can apply
    US

    Listing Details

    Posted
    May 12, 2026
    First seen
    May 12, 2026
    Last seen
    July 3, 2026

    Posting Health

    Days active
    53
    Repost count
    0
    Trust Level
    18%
    Scored at
    July 4, 2026

    Signal breakdown

    freshnesssource trustcontent trustemployer trust
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    Senior Fraud Risk Analyst