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Head of Portfolio Analytics
- New York, New York, United States
- New York, New York, United States
Über
Head of Portfolio Analytics
role at
Grasshopper Bank
Department:
Credit
Location:
Remote
Grasshopper Bank is a client‑first, digital bank built for the business and innovation economy, with an obsession for providing leading‑edge technology, solutions‑driven products and superior service through a combination of passionate people and digital resources. We are a highly experienced team who pride ourselves on diversity of thought and perspective. Nationally chartered, our portfolio of products and services range from VC, PE & Portfolio Companies to SBA Lending, as well as direct SMB and Embedded Banking. Our entrepreneurial drive allows us to support the growth and success of a wide range of clients at every stage of their business through inclusive partnership. We seek out team members who will enable both our organization and our people to grow and thrive through collaboration and acting with integrity and respect. Our focus on cross‑functional teamwork provides a culture where ideas are valued, accountability is encouraged, and successes are celebrated. We welcome all those searching for the opportunity to contribute to banking innovation that influences and supports the emerging digital world of Financial Services. Our digital first approach enables our teams the flexibility to work remotely. We have offices in NYC and Boston.
What You'll Do We are looking for a hands‑on, strategic leader to build and own the analytical "brain" of our credit portfolio. As the Head of Portfolio Analytics, you will be the bridge between raw data and business strategy. You will move beyond simple reporting to answer the "so what?"—using data to optimize our credit buy box, forecast losses, and drive profitability for our digital lending products. At a small digital bank, we don't just manage risk; we engineer it. You will work cross‑functionally with Product, Engineering, and Finance to ensure our portfolio scales safely and efficiently.
Responsibilities
Portfolio Intelligence: Design and maintain the "source of truth" dashboards and reports that track portfolio health, vintage performance, delinquency trends, and unit economics.
Credit Strategy Optimization: Analyze approval rates, line assignments, and pricing elasticity to recommend changes to our credit policy (the "Buy Box").
Loss Forecasting & Provisioning: Own the models for allowance for credit losses (ACL/CECL) and stress testing.
Data Infrastructure: Partner with Data Engineering to define data schemas and pipelines. You will likely be the primary "power user" of our data warehouse, ensuring data integrity for analysis.
Unit Economics: Deep dive into profitability at the customer and segment level, ensuring we are acquiring and retaining the right kind of volume.
Monitor: Track Key Performance Indicators (KPIs) such as NCOs (Net Charge‑Offs), Delinquency Roll Rates, and Risk‑Adjusted Return on Capital (RAROC).
Iterate: Propose and test new credit strategies (e.g., "challenger" models) to expand approval rates without compromising risk appetite.
Report: Present monthly Portfolio Review materials to the Executive Committee and Board of Directors, translating complex data into clear business narratives.
Collaborate: Work with the Product team to embed risk analytics into the customer journey (e.g., real‑time credit limit increases).
Lead: As the bank grows, hire and mentor a high‑performing team of data analysts and data scientists.
What You Need You are a "player‑coach"—someone who can present to the Board in the morning and write complex SQL queries in the afternoon. You are not waiting for a support team to pull the data; you are comfortable getting your hands dirty.
Experience: 7+ years in credit risk analytics or portfolio management. Experience at a fintech or challenger bank is a massive plus.
Technical Stack: Advanced proficiency in SQL and Python/R for modeling. Expert‑level knowledge of visualization tools (Tableau, Looker, or PowerBI). Experience with nCino and IBS. Desire to integrate AI into our daily underwriting and portfolio management process.
Domain Knowledge: Deep understanding of credit lifecycle (origination to collections), vintage analysis, and lending regulations (e.g., Fair Lending, TILA).
Education: Bachelor’s or Master’s degree in a quantitative field (Statistics, Economics, Math, Engineering, or similar).
Seniority Level Director
Employment Type Full‑time
Job Function Business Development and Sales
Industries Banking
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Sprachkenntnisse
- English
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