Real-posted 3 days ago
Full-time • Manager
Newark, CA
251-500 employees

We are looking for a data-driven Credit Risk Manager to build the analytical backbone of Real Wallet Capital - our dynamic line of credit for real estate agents. This is not a maintenance role; it is a build role. You will be the primary owner of credit analytics, responsible for translating raw data into risk policies, pricing strategies, and loss forecasting models. You will help us scale a safe, innovative, high-growth lending business from the ground up. If you are an AI, SQL, and Python-native analyst who loves credit strategy, thrives in ambiguity, and wants to shape the future of financial products for real estate agents, we want to hear from you.

  • Build the Risk Engine: Develop and own the analytical framework for credit risk, including underwriting models, loss forecasting, and credit policy definition using SQL and Python.
  • Monitor Portfolio Health: construct comprehensive dashboards (Sigma, Looker, or similar) to track repayment behavior, vintage performance, delinquency roll rates, and unit economics.
  • Drive Strategy & Optimization: Analyze product performance to recommend data-backed changes to product designs that maximize funding availability while protecting downside.
  • Lead New Product Analysis: Conduct deep-dive assessments on market segments and risk profiles to help design and launch future financial products for real estate agents.
  • Automate & Innovate: Leverage AI tools (ChatGPT, GitHub Copilot) to accelerate code generation and insight discovery, moving our risk processes from manual reviews to automated decisioning.
  • Collaborate Cross-Functionally: Partner closely with Product, Finance, and Operations leadership to translate complex risk data into clear, actionable business strategies.
  • Technical Fluency: Strong proficiency in SQL and Python is required; you must be comfortable querying raw data and building your own analytical models.
  • Credit Domain Expertise: A solid grasp of credit risk principles for SMB or consumer lending, including repayment modeling, vintage analysis, and concentration risk.
  • Visualization Skills: Experience building dashboards and analytical tools using platforms like Sigma, Looker, Tableau, or Metabase.
  • High-Leverage Toolkit: Ability to utilize AI tools to dramatically increase speed and output quality in a lean environment.
  • 0 to 1 Mindset: You thrive in ambiguity and are energized by building processes from scratch rather than just managing existing ones.
  • Clear Communication: Exceptional ability to simplify complex quantitative findings into clear written and verbal narratives for executive stakeholders.
  • Bachelor’s degree in a quantitative or analytical field (e.g., Economics, Finance, Mathematics, Statistics, Engineering, or Computer Science).
  • 3+ years of experience in credit risk, analytics, fintech lending, specialty finance, or adjacent fields.
  • Experience in a high-growth startup or fintech environment is a strong plus.
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