Senior Risk Analyst

Truss; Austin (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Truss is hiring a Senior Risk Analyst in Austin, TX to join a hands‑on IC role focused on fraud prevention and risk controls. You will investigate and disposition risk, tune规则 and signals, and partner with product and engineering to ensure secure money movement.

The position emphasizes owning detection loops and actionable feedback into policy. The ideal candidate has 3–4+ years in fintech risk, strong SQL skills, and the ability to explain judgments clearly while prioritizing customer and

Qualifications

• 3–4+ years in fraud or payments risk within fintech, payments, or banking.
• Hands-on experience with money movement and abuse patterns.
• Proficiency in SQL to pull cases and measure rule performance.
• Clear written judgment on held, released, or escalated cases.

Responsibilities

• Investigate and disposition risk across queues for payment fraud and abuse.
• Tune rules, signals, and thresholds; assess precision and impact.
• Own detection, review, and action loops; document dispositions for policy/automation.
• Collaborate with product, engineering, and compliance on onboarding, ledger, payments, and cards.
• Balance false positives/negatives to protect both business and customers.

Skills

Fraud detection

SQL

Python

Risk management

Tools

Sift

Alloy

Unit21

Job description

About The Role

Truss is a regulated fintech: real bank accounts, real money movement, cards, payables, receivables. Risk is not a side quest. Every dollar we move is a decision — onboard or don't, pay or hold, release or review — and those decisions have to be fast, sharp, and defensible. We're hiring a Senior Risk Analyst — an individual contributor who lives in the queues, the rules, and the loss curve. You investigate fraud and abuse, tune controls, and partner with product and engineering so good merchants get paid and bad actors get stopped. This is not a Head of / founding-exec seat. It is a hands‑on IC role for someone who has already done the work at a payments or fintech company and wants to do it in Austin, close to the product.

What You’ll Actually Do

• Investigate and disposition risk. Work merchant and transaction queues: payment fraud, check fraud, account takeover, synthetic identity, mule activity, first-party abuse, and edge cases in ACH, wires, cards, and payouts. Clear cases with crisp, defensible reasoning.
• Tune rules and signals. Propose and test rule changes, velocity checks, identity and device signals, and review thresholds. Measure precision/recall and dollar-weighted impact — not vibes.
• Own detection > review > action loops. Keep queues from becoming black holes. Document dispositions so they feed back into policy and automation. Escalate patterns that need a product or engineering fix.
• Partner with product, engineering, and compliance. Sit with the people who ship onboarding, ledger, payments, and cards. Coordinate BSA/AML- and OFAC-aware patterns with compliance — you don't outsource judgment to a PDF.
• Protect the business and the customer. False positives kill good contractors. False negatives kill the company. Hold both. Trade loss rate, approval rate, and ops cost with eyes open.
  

What We’re Looking For

• 3–4+ years in fraud, payments risk, merchant risk, or trust & safety at a fintech, payments, or banking company — ideally in a production queue / rules environment (not pure advisory).
• Hands‑on fluency in how money moves and how it gets stolen: ACH, wires, checks, cards, account funding, payouts, and common abuse patterns.
• Comfort with SQL (or similar) to pull cases, segment risk, and measure rule performance.
• Clear written judgment: you can explain why you held, released, or escalated a case.
• Bias toward ownership in a small team — you take the case, make the call, and follow the metric.
• Must be legally authorized to work in the U.S. (no sponsorship).
• Based in Austin, TX (in‑person).

Nice to Haves

• Experience with tools like Sift, Alloy, Unit21, or a homegrown rules/decisioning stack.
• Exposure to KYC/KYB quality, transaction monitoring, or sponsor-bank / program‑manager expectations.
• You’ve lived through a real fraud spike or bank‑partner fire drill and helped fix it.
• Enough Python (or similar) to prototype analyses quickly.