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At Cardless, we’re building a credit card and loyalty platform that consumer businesses use to engage their customers. We’ve launched 14 credit cards, including for Alibaba and Qatar Airways. We help businesses bring imaginative card programs to life, and have pioneered technology to embed credit card features natively into their products.
We value curiosity, humility, and intensity — we move fast and take ownership. This is a place where a motivated, resourceful individual can have an enormous impact on our trajectory. We're headquartered in San Francisco, and have raised about $90M in equity funding from top venture capital firms and angels.
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About the Job
The Credit Risk Lead at Cardless will oversee credit risk management across all our partner brands. This includes leading initiatives around originations (such as credit policy, initial line assignment, and risk-based pricing), account management (e.g., CLI, CLD, Authorization), collections strategies, reporting, loss forecasting, and advanced analytics. In this role, you will develop and implement tools to scale risk management processes as we grow our partnerships.A strong sense of responsibility is key: you will foster open communication, address concerns proactively, and ensure adherence to policies and procedures. Additionally, you'll align with Cardless' risk appetite while balancing customer experience and operational objectives. As the company scales, you'll be accountable for identifying, managing, and reporting risks across all areas of the business.
Responsibilities
- Lead the development and execution of credit risk strategies for both new and existing brand partners.
- Conduct advanced analytics, including customer segmentation, optimization, predictive analytics, and machine learning, to manage risk and detect fraud.
- Expand the data used in credit decisioning by leveraging proprietary risk models and evaluating third-party data sources.
- Build and maintain automated dashboards to track key performance indicators (KPIs) around originations and portfolio performance, presenting insights to senior management.
- Design and execute A/B tests to evaluate new strategies, balancing product performance with customer and partner satisfaction.
- Collaborate with the Compliance team to ensure all credit risk strategies align with fair lending regulations and principles.
- Develop and maintain loss forecasting models to predict charge-offs and recovery rates across different delinquency stages.
- Develop and maintain comprehensive Credit Policy manuals and underwriting procedures.
- Partner closely with Engineering, Product, and Operations teams to assess operational feasibility and launch MVPs, iterating quickly based on performance.
Requirements
- Bachelor's or Master’s degree in a STEM field or Economics, with a focus on data-driven problem solving (preferred).
- 7+ years of experience in credit risk within the consumer credit industry.
- 4+ years of hands-on experience using R, Python, SAS, and SQL to analyze large, complex datasets.
- 2+ years of experience in quantitative analysis within a fintech startup.
- Strong knowledge of the consumer credit landscape and familiarity with fair lending regulations such as ECOA, FCRA, and TILA.
- Proficiency with BI/data visualization tools (e.g., PowerBI, Tableau) to create clear, actionable dashboards.
- Experience designing and implementing A/B testing to assess new strategies.
- Familiarity with data pipelining, data modeling, and ETL processes.
- Ability to thrive in a fast-paced, high-volume environment while managing multiple tasks simultaneously.
- Strong communication and presentation skills, with the ability to convey complex analyses clearly.
- Experience working with banking partners and third-party data vendors is a plus.
Benefits
We're headquartered in San Francisco, CA, with a beautiful office in the Mission District. We're proud to offer our team excellent benefits:
💸 Meaningful Start-up equity
🏥 100% health, vision & dental primary coverage
➕ 75% health, vision & dental dependent coverage
🍱 Catered lunches
🚎 $250/month Commuter benefit
👶 Parental leave
✈️ Team building events & happy hours
🌴 Flexible PTO with a minimum of 15 days off per year
🖥️ Apple equipment
💸 401k plan
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Cardless employees are required to be fully vaccinated and boosted against COVID-19, and to provide proof of vaccination prior to their first day. Cardless is an equal opportunity employer, and we value a diverse and inclusive workplace. We do not discriminate on the basis of race, national origin, ethnicity, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other applicable legally protected characteristics.
Cardless San Francisco, California, USA Office
Our office is located in the trendy Mission District and is close to multiple transportation stations. After work, head down to Valencia street for happy hours or to explore the fun restaurants and shops. Or cross the street to see some of the most iconic views of SF from Mission Dolores Park.
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
