Credit & Risk Analysts: $65-$160/hr from Frontier AI Labs

Open application· 47 spots this round

$65-$160/hr credit and risk analysis work, on your schedule

Review AI-generated credit memos, underwriting, and risk models the way you'd review a deal before committee. Flag the optimistic projection, the covenant that won't hold, the risk the spreadsheet hides. The instinct for which borrowers actually pay back is what AI labs need on the record.

Fully remoteYour scheduleWeekly pay

Apply nowApply once, get matched on a rolling basis. No prior AI experience needed.

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Hi, we're Zac and Jack, the founders of Terac. We want to talk to you directly, because you are the most important part of what we're building.

Terac is a community of experts. People who have spent years getting good at something specific and hard. The world is about to need more of you, not less. As AI takes on more of the world's work, the bottleneck shifts to the people who actually know what they're talking about.

Expert labor is the rarest resource in the world right now, and it is shockingly hard to find. The companies that need a credit analyst's eye on a memo that buries the risk spend weeks chasing people, paying placement fees, and settling for whoever is available. Meanwhile thousands of qualified people are sitting with knowledge that no one ever asks for.

That gap is what we're here to close. Every project that lands on Terac is routed to the people who actually know the answer, on their schedule, paid fairly, and only when the work is verified. No middleman taking a cut of your time. No vague gigs. No chasing checks.

We care about every single person in this community. If you join Terac, you're not a row in a database to us. We read the feedback. We answer the emails. We will fight for you when a customer is being unreasonable, and we will be honest with you when something on our side is broken. The quality of this panel is our entire company, and we owe you a serious bar.

If you've made it this far, here is what we're asking: claim your profile. Put your expertise on the record. Let the world's most ambitious teams come find you for the work only you can do.

Zac & Jack

Founders

Credit & Risk questions

Still curious? Write to us at support@terac.com.

Narrow specialization is an advantage, not a liability. AI models struggle most at the edges of a domain, so work on leveraged loan covenant analysis, CLO waterfall mechanics, or ABS performance attribution is actively in demand. The more specific your background, the more precisely we can match you to opportunities where your knowledge directly improves model quality.

Both credentials qualify and neither is preferred over the other for most engagements. A CFA charterholder doing corporate credit analysis and an FRM holder running counterparty credit risk models are equally valuable depending on the task. What matters is that the credential reflects active professional practice, not just a passed exam.

No. The work involves reviewing AI-generated credit analysis, rating model rationale, or risk narratives against your own professional judgment. You are never asked to produce regulatory capital calculations, sign off on model validation outputs, or take any action that would carry an institutional liability. You apply your expertise as a subject-matter reviewer, not as a credentialed officer of any institution.

Tasks include evaluating AI-written credit memos and obligor summaries for accuracy and reasoning quality, annotating probability-of-default or loss-given-default model outputs to flag where the AI misapplied CECL methodology or got the risk driver wrong, and creating worked examples that show how an expert structures a credit argument from financial statement data. Screener modeling, portfolio stress-test narratives, and covenant compliance analyses also come up.

Both matter. Conceptual tasks like evaluating a model's written rationale do not require you to have a specific tool open, but some engagements specifically need reviewers who can spot errors that only surface when you know how a tool like RiskCalc or S&P Global Market Intelligence constructs its output. When a task requires tool familiarity, it will be stated in the project brief so you can self-select accurately.

Why your expertise matters

Credit and risk analysis sits at the intersection of quantitative modeling, regulatory interpretation, and judgment calls that resist formulaic answers. AI models trained on generic finance text routinely misapply probability-of-default frameworks, confuse IFRS 9 staging criteria, or produce covenant analysis that looks plausible but would never survive a credit committee. Only a practitioner who has built and defended a credit memo, stress-tested a leveraged buyout model, or navigated a Basel III RWA calculation can reliably distinguish a defensible model output from a confident-sounding mistake.

How pay works

Hourly rates toward the $160 end reflect specialization depth: professionals with direct experience in structured credit, leveraged finance, or regulatory capital (CRR3/Basel IV) consistently command higher rates than generalist commercial lending reviewers. All work is fully remote, billed by the verified hour, and payment releases only after Terac confirms task completion - there are no retainers, no unpaid auditions, and no minimum weekly commitments.

What the work looks like

A sample of the credit and risk analysis work you would pick up. Every project is scoped, remote, and paid on verified completion.

Review an AI-generated credit memo for a mid-market industrial borrower and flag reasoning errors in the leverage and coverage analysis that a credit committee would reject.
Evaluate a model's IFRS 9 stage migration analysis for a portfolio of retail mortgages, identifying where the significant increase in credit risk (SICR) triggers are misapplied.
Write a worked example of a leveraged buyout debt sizing analysis, showing step-by-step how a senior credit officer would set covenant thresholds relative to base-case EBITDA projections.
Annotate a set of AI-produced CRE underwriting summaries, scoring each for adherence to DSCR, LTV, and debt yield benchmarks and noting where market comparables were incorrectly applied.
Compare two AI-generated Basel IV standardized approach RWA calculations for the same corporate exposure and explain which inputs led to the divergent capital requirement outputs.
Create a realistic stress-test narrative for a syndicated loan portfolio under a rising-rate, declining-GDP scenario, structured so it can serve as a reference example for model evaluation.