Credit Risk Analyst

One out of every two small businesses fails within their first five years, most often due to running out of cash. Quick Books Capital is on a mission to make a dent in that statistic, by providing small businesses access to the capital they need when they need it, leveraging the data inside Quick Books for faster and better decisioning. This way, our customers never again have to worry about not making payroll or saying no to a business opportunity.

That’s how we power prosperity.

Quick Books Capital is a nimble and high-priority start-up within Intuit that is looking to reinvent small business borrowing. We are the fastest growing SMB lending business in the market. We are looking for top talents and team members that love new challenges, cracking tough problems and working cross-functionally. If you are looking to join a fast-paced, innovative and incredibly fun team, then we encourage you to apply.

A Staff credit risk lead will play a critical part in driving business growth through the following responsibilities:

• Lead new lending business initiatives from a credit risk strategy perspective, bringing innovative ideas to optimize processes, maximize customer value, and fuel business growth—all while ensuring alignment with Capital’s P&L goals.
• Proactively identify opportunities for enhancement across the customer lifecycle. These opportunities are not limited to credit risk, but extend to every customer touchpoint. Take ownership from ideation to execution, driving measurable business outcomes.
• Monitor portfolio performance regularly, analyze trends, and clearly communicate insights and recommendations to stakeholders and senior leadership.
• Collaborate with the data science team to design and implement innovative risk solutions, leveraging the latest technology to meet Quick Books customers’ financing needs.

• Develop complex credit strategy proposals for front end credit risk management. Use data-driven storytelling to build compelling cases and persuade diverse audiences.
• Apply strong analytical and strategic thinking skills to build sound assumptions, validate hypotheses, and structure proposals within a clear, logical framework.
• Manage and monitor policy and portfolio performance, extracting meaningful insights and preparing reports that drive alignment and action among stakeholders and senior leadership.
• Foster an innovative mindset by continuously identifying opportunities in credit, product experience, customer targeting, and beyond; to drive growth and simplify processes.
• Demonstrate ownership and leadership by collaborating with cross-functional partners (product development, product management, marketing, data engineering, compliance, underwriting, etc.) to design new products and expand market share.
• Influence and align cross-functional teams to transform ideas into tangible business outcomes.
• Work closely with data science, underwriting, and data engineering teams to enhance customer segmentation, develop innovative credit strategies, and conduct portfolio analyses.
• Leverage big data technologies to analyze large-scale transactional data, turning insights into actionable opportunities for credit risk management and business growth.
• Design, implement, and monitor tests to explore new methodologies, measure key metrics, and refine acquisition strategies and credit policies.

• MS/PhD in a quantitative field such as Statistics, Operations Research, Industrial Engineering, Economics, etc., or a Bachelor’s degree in the same fields with 3+ years of relevant work experience.
• 6+ years of professional experience in an analytics-related role; lending or fintech experience is strongly preferred.
• Proven track record of extracting actionable business insights from data using both quantitative and qualitative approaches.
• Proficiency in at least one analytics tool, such as Python, R, or SQL.
• Advanced Excel skills, with strong logical thinking and expertise in SQL/relational database queries.
• Familiarity with big data technologies such as Hive, Hadoop, and related frameworks.
• Domain knowledge in credit risk, including areas such as credit bureau attributes and scoring, scorecard…