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Risk Analyst

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Remote from
USA
Salary
USD 120k–145k / yr
Employment
Full Time
Experience
Open level
Published
Apply before
17 Nov 2026
Listing views
13
Application actions
1
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AI Summary

The role, at a glance.

Flex is hiring a Risk Analyst to improve credit underwriting, portfolio monitoring, fraud detection, and risk-informed product decisions for an SMB-focused financial platform. The role analyzes applicant financials, bank and accounting data, credit bureau reports, payment behavior, and delinquency trends. It also supports unsecured credit-card P&L analysis, customer profitability modeling, and loss-driver identification. Candidates need at least five years of credit or data analytics experience, strong SQL or SAS capabilities, and working proficiency with Python or R. Success requires translating complex risk findings into clear recommendations for cross-functional stakeholders.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThis is a senior analytical role requiring applied credit-risk judgment across underwriting, portfolio management, financial-statement analysis, and product economics. The fast-moving fintech environment and responsibility for real-time credit decisions add meaningful complexity.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$132,500
US market range (per year)$115k–$155k
AI insightThe employer discloses a yearly base-compensation range of $120,000–$145,000 USD, with a midpoint of $132,500. This is a credible range for a US-based Risk Analyst with 5+ years of fintech, lending, or credit-card analytics experience. Estimated US market compensation for comparable roles is $115,000–$155,000 per year; equity may be offered separately.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you evaluate a new SMB credit applicant using financial statements, banking data, and bureau information?

I would first validate data quality and reconcile key metrics across the P&L, balance sheet, tax documents, and banking feeds. I would assess revenue consistency, cash-flow volatility, leverage, liquidity, payment obligations, bureau history, and adverse signals, then combine these factors into an underwriting recommendation with clear approval terms or risk mitigants.

What leading indicators would you monitor to detect deteriorating creditworthiness after origination?

I would monitor changes in cash inflows, spend patterns, utilization, payment timing, returned payments, bank-balance trends, engagement, and newly reported bureau events. I would segment customers by risk profile and vintage so that deviations from expected behavior can trigger early-review or collections workflows.

Describe how you would use SQL and Python together for a portfolio-risk analysis.

I would use SQL to build reliable account-level datasets by joining transaction, payment, underwriting, and external credit data. In Python, I would perform exploratory analysis, cohort and survival analysis, feature creation, and visualization, then document findings and productionize repeatable reporting where appropriate.

How would you assess the profitability of an unsecured business credit-card customer segment?

I would estimate segment-level revenue from interchange and interest, then subtract rewards, servicing, funding, fraud, and expected credit-loss costs. I would compare risk-adjusted contribution margins, retention, utilization, and lifetime value across cohorts to identify segments where underwriting or pricing changes could improve returns.

Tell us about a time you communicated a complex risk finding to a nontechnical stakeholder.

I would explain the business decision first, then present the few metrics and trends most relevant to that decision using a concise visual or dashboard. I would clearly state the level of confidence, assumptions, recommended action, and expected trade-offs so stakeholders can act without needing to interpret the underlying model logic.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

Flex is building the AI-native private bank for business owners.

We’re re-architecting the entire financial system for entrepreneurs—from the first dollar a business earns to how that value compounds, moves, and is ultimately spent in real life. Banking, credit, payments, personal finance, and financial operations—rebuilt from the ground up as a single, intelligent system. Flex is the full financial home for ambitious owners.

Since launching publicly in September 2023, Flex has scaled from zero to nine-figure annualized revenue, with a clear path to profitability by late 2026. We move fast, ship relentlessly, and operate with extreme ownership.

Our customers are affluent business owners ($3–$200M in revenue)—the backbone of the economy and one of the most underserved segments in finance. They’re stuck with outdated banks and fragmented tools. We’re replacing all of it. The opportunity is massive: a ~$1T+ revenue market hiding in plain sight. Our ambition is to build a $100B+ company by delivering a product that is fundamentally better—not incrementally improved.

Flex has raised $100M+ in equity and $300M+ in debt.

– Mission-critical problems: We build software that directly controls how money moves at scale.

– High bar, low ego: Small teams, exceptional people, real ownership.

– Speed over comfort: We prioritize execution, quality, clarity, and results.

– Enduring impact: What we’re building will define how a generation of owners runs their businesses.

Team & Locations

We hire exceptional people who want to build hard things and see their work matter immediately. Roles are available in: San Francisco, Miami, New York, and fully remote.

Flex Fuels Ambition.

About the Role

We are seeking an energetic and intellectually curious Analytics professional with domain expertise in credit analytics and a strong grasp of financial data interpretation. The ideal candidate will be comfortable working with varied datasets to derive insights for both credit underwriting and ongoing portfolio management. This role will play a critical part in improving credit decisions, monitoring customer behavior, and informing risk management and product strategy.

What You’ll Do

New Account Evaluation

  • Analyze new applicant data to support automated and manual credit decisioning.
  • Work with data extracted from business financial statements, tax documents, and banking integrations (e.g., Quickbooks, Netsuite, Plaid, etc).
  • Leverage insights from adjacent product usage (e.g., business banking, payments platforms) to evaluate risk profiles.
  • Build dashboards or tools to surface real-time indicators for underwriting and fraud detection.

Existing Account Management

  • Monitor account-level behavior post-origination, including spend and payment patterns, credit utilization, and engagement.
  • Identify signs of weakening creditworthiness using internal data and third-party credit reports (e.g., Experian, D&B).
  • Track and analyze delinquency trends and payment consistency to refine risk models and collections strategies.
  • Develop behavioral segments and performance cohorts for proactive account management.

Credit Product P&L Understanding

  • Support P&L analysis of the unsecured credit card product, including interchange income, interest revenue, rewards cost, and charge-off rates.
  • Build models to evaluate customer lifetime value, profitability segmentation, and risk-adjusted returns.
  • Assist in identifying drivers of loss and opportunities for margin improvement.

Requirements

  • 5+ years of experience in a data analytics or credit analytics role, preferably within fintech, credit cards, or SMB lending.
  • Fluency in SQL / SAS and comfort with Python or R for exploratory data analysis and automation.
  • Strong understanding of credit underwriting principles and SMB financial analysis.
  • Experience interpreting business financials (P&L, balance sheet, tax returns) and cash flow data from banking sources.
  • Familiarity with credit bureau data and commercial credit reports.
  • Ability to communicate findings clearly and influence cross-functional stakeholders.

Compensation

Final compensation within this range will be based on experience, qualifications, and interview performance. This position is also eligible for equity compensation. Flex offers medical, dental and vision insurance, paid time off, and a 401(k) plan. Applications will be accepted on an ongoing basis until the position is filled.

Additional Information

Why Join Us

Build something generational — Capture the full lifecycle of money for ambitious business owners.

Work on real money, real risk — Payments, credit, and banking at serious scale.

Solve hard problems — AI, underwriting, compliance, and global finance from first principles.

True ownership — Small teams, high trust, real accountability.

Founder-level exposure — Direct access to leadership, customers, and investors.

High bar, high taste — Move fast without cutting corners.

Elite peers — People here are builders, not tourists.

Real upside — Meaningful equity if you help build something big.

Apply now >

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