Sr. Fraud Analyst

United States Digital Space LLC

New York (NY)

Hybrid

USD 135,000 - 160,000

Full time

14 days+

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Benefits offered by this job

Medical, dental, vision
Life/AD&D insurance
401(k) match
Equity
Sabbatical after 6 years

Job summary

United States Digital Space LLC is seeking a Senior Fraud Analyst in NYC to own customer risk rating, KYC, and fraud monitoring models. You will partner with Data, Compliance, and Product to design controls and advise leadership on model performance.

The role is based in our NYC office with a hybrid schedule (four days in-office, with seasonal flexibility). Salary ranges reflect NYC market norms and may include incentive bonuses.

Qualifications

  • 3–5+ years in fraud prevention, analytics, and financial crime.
  • Direct experience with fraud patterns/controls (ATO, ACH, card fraud, KYC/KYB).
  • Strong data-driven approach with ability to interpret model performance.

Responsibilities

  • Manage Fraud rule sets and controls across the customer journey.
  • Monitor data analytics to refine rules and reduce false positives.
  • Design new rules to address emerging fraud patterns and improve detection.

Skills

SQL
Fraud analytics
KYC/AML
Risk scoring
Data-driven

Job description

About the company

the company is a leading, technology-driven financial services company that offers investing, savings and retirement solutions for retail investors and investment advisors as well as financial wellness solutions, including a 401(k) for small and medium-sized businesses. Our team is passionate about our mission, to empower people to build wealth with confidence and ease. We’re headquartered in NYC and offer hybrid NY-based positions (four days/ week in-office, with no required office days during the summer and winter holidays).

About the Role

the company’s Risk Operations team plays a critical role in protecting our platform and customers from fraud and financial crime. As a Senior Fraud Analyst, you will be the analytical owner of our customer risk rating, KYC, and fraud monitoring models. You will use data to shape how we detect, prevent, and respond to emerging fraud trends.

You will partner closely with Data, Compliance, and Product to design controls, build monitoring, and regularly advise leadership on model performance, threats, and residual risk.

This role is based out of our NYC office. Below we've reflected the base salary range for this position. Actual salaries may vary depending on factors including but not limited to location, experience, and performance. The range listed is just one component of the company’s total compensation package for employees.

  • New York City: $135,000 - $160,000

This job may also be eligible for variable compensation in the form of a company incentive bonus.

A Day in the LifeManage Fraud rule sets and controls
  • Set up and perform continuous rule performance monitoring
  • Utilize data analytics to refine rules and reduce false/positives
  • Design new rules to address emerging fraud patterns and detect suspicious activity
  • Identify and remedy control gaps
Influence architecture builds and data integration
  • Orchestrate fraud monitoring through full customer journey across payment rails, funding flows, logins, and behavioral signals.
  • Strengthen case management process
  • Partner with Engineering for data harvesting, analytics and rule implementation
  • Lead cross‑functional projects from problem definition through implementation and post‑mortem, ensuring stakeholders are aligned on goals, timelines, and outcomes.
  • Identify, implement and assess vendor solutions
Own customer risk and KYC models
  • Maintain and enhance customer risk rating, signup, and related fraud scoring models.
  • Define clear model performance metrics (e.g., detection rate, false positive rate, lift) and establish monitoring to track drift over time
Partner with Customer Experience team
  • To identify friction points, customer abandonment, and true cost of fraud prevention
  • Reduced account locks, allow faster money movements, and lower ID request rates while not increasing fraud
  • Increase customer greenlight passes and ensure manual reviews provide strong controls
Build monitoring and reporting
  • Partner with Data/Analytics to build dashboards that surface fraud KPIs, trends, model health, and control coverage for a variety of stakeholders (Ops, Compliance, Product, Leadership).
  • Create recurring reporting packages for FraudCo and Risk leadership, translating complex analysis into clear recommendations.
What We’re Looking For:
  • Experienced Fraud Professional: 3–5+ years in fraud prevention, analytics, and financial crime (fintech, banking, brokerage, or payments). Must have direct experience with fraud patterns/controls (e.g., ATO, ACH/transfer, card fraud, KYC/KYB, synthetic identities).
  • Data-Driven & Technical: Advanced SQL is required. Comfortable framing analytical questions, designing experiments, and interpreting model/rule performance.
  • Familiarity with Fraud ecosystem (solutions, capabilities, challenges)
  • Model/Control-Oriented: Understands fraud stack components (risk models, rules, signals). Able to design monitoring for model drift, data quality, and control failures. Knowledge of KYC/AML, customer risk rating, and step-up auth/verification.
  • Strong Communicator & Project Driver: Excellent communication; can translate complex analytics and risk trade-offs to technical/non-technical audiences. Comfortable presenting to senior stakeholders and committees. Demonstrated end-to-end project management skills.
  • Collaborative & Practical: Enjoys cross-functional problem-solving (Ops, Data, Eng, Compliance, Product). Balances fraud loss, CX, and efficiency. Stays current on emerging fraud trends and brings new ideas.
Join a team built on these core valuesWe change lives

Be a part of a community of innovators working to transform financial outcomes for real people. Your work will make an impact, always laddering up to our mission; to empower people to build wealth with confidence and ease.We set audacious goals

We set them for the company, our customers, and ourselves, and we won’t stop until we reach them. We don’t just show up; we give our all, then celebrate our wins.

We value all perspectives

When we collaborate, we're at our best. We believe diverse perspectives lead to better outcomes and strive to uphold our supportive and inclusive community.

We simplify financial services

We’re financial services pioneers, always finding new ways to improve, optimize, and enhance. Constant improvement is in our DNA.

Our Commitment to Your Total Well-being:
  • We offer a competitive suite of benefits, including medical, dental, and vision coverage; life and AD&D insurance; short-and long-term disability; infertility support and WPATH-aligned transgender health benefits; an Employee Assistance Program (EAP); transit benefits and FSA and HSA options
  • Ownership: Equity for all employees, including new hire and refresher grants.
  • Time: Flexible paid time off, paid parental leave, and a fully paid four-week sabbatical in your sixth year.
  • Growth: Company-paid professional coaching for all employees.
  • Wealth: Day-one 401(k) match plus matching on qualified student loan payments.
What happens next

We’ll take a few weeks to review all applications. If we’d like to spend more time with you, we’ll reach out to arrange next steps, which will include 3-4 sets of meetings with your future colleagues.

In the interview process, we’ll look to learn more about your skills, experiences, capabilities, and motivators. Many of our questions will be aimed at understanding how you might operate here at the company. Depending on the role, we may ask you to complete a case study exercise or technical assessments, as we want to collect a robust set of data points to better inform our decisions.

On average, it takes us around 3-5 weeks to make a hiring decision, depending on your availability and sense of urgency. As a best practice, we aim to interview at least 2-3 final round candidates before making a hiring decision. Please note that, as we usually re

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