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Senior Credit Analyst

Cleo
Remote, USA
Full-time
Mid · 3–5 years experience
Remote
USD 170000-210000 yearly / year
Discovered 3 days ago
SQLPythonPandasNumPy

Full Job Posting

Meet the team 👥

Here at Cleo we have team of ~135 member in our Borrow Pillar and ~8 dedicated to Credit Policy and Analytics. This function brings together several specialisms, all working toward managing portfolio performance; designing the systems, models, and controls that make lending sustainable. They drive to build and grow a portfolio of responsible EWA & Pay Later products that can scale across markets while protecting users from high cost debt trap.

About the role ✍️

We're hiring a Senior Credit Risk Analyst to help build our next generation of credit underwriting models and strategy, within Credit Policy & Analytics . You'll work at the heart of our credit expansion - supporting EWA (scaling 2x every year) and new launches like BNPL across the US and UK.

Use Cleo's proprietary and third-party data to reduce loss rates and improve customer experience

Optimise risk thresholds, policies, and strategy to expand member access and eligibility for our credit products

Apply quantitative analytics to understand risk drivers and recommend mitigation strategies

Build dashboards to monitor and report on credit product performance

Design, run, and analyse experiments across our credit product

Apply state-of-the-art techniques to combat and mitigate fraud risk

Influence credit policy, portfolio performance, and customer outcomes directly through your analysis, with exposure to senior stakeholders across the business

What we're looking for 🕵️

Bachelor's degree in Engineering, Math, Finance, or another quantitative discipline; Master's is a plus

3-5 years of analytical experience, preferably in a credit risk role at a FinTech company

Experience designing lending products compliant with US state and federal regulations

Experience with SQL, Python, or other statistical modelling tools

Advanced Microsoft Excel skills

Experience adopting AI tools within day-to-day work

Experience/knowledge of working with A/B testing

Nice to have: experience with Python for data analysis (Pandas or NumPy)

Nice to have: knowledge of state-of-the-art machine learning techniques

What we offer

  • We offer benefits package built to support you in and out of work. Benefits vary by country 🌍 and include meaningful equity, comprehensive health insurance, mental health support, a paid one-month sabbatical after four years, a learning & development platform, pension or retirement contributions, and location-specific leave entitlements. For the full breakdown on what's available in your location, visit our Candidate Hub 👈

What Matters

Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their merits.

We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know.

We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!

Requirements

  • Bachelor's degree in Engineering, Math, Finance, or another quantitative discipline; Master's is a plus
  • 3-5 years of analytical experience, preferably in a credit risk role at a FinTech company
  • Experience designing lending products compliant with US state and federal regulations
  • Experience with SQL, Python, or other statistical modelling tools
  • Advanced Microsoft Excel skills
  • Experience adopting AI tools within day-to-day work
  • Experience/knowledge of working with A/B testing
  • Nice to have: experience with Python for data analysis (Pandas or NumPy)
  • Nice to have: knowledge of state-of-the-art machine learning techniques

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