Design, build, and maintain a suite of dashboards that track deal/asset performance, risk, and key portfolio KPIs (e.g., collateral performance, delinquency, prepayment, loss metrics, triggers/covenants, concentrations, vintage curves).
Build a unified web portal / internal site where dashboards, reports, and self-serve analytics tools are organized, versioned, and accessible with appropriate permissions.
Act as point of contact for third party data providers to help normalize, and validate deal-level data.
Support ad-hoc analysis for investment memos, portfolio reviews, and ongoing surveillance.
Own project plans and delivery cadence: scope, milestones, dependencies, and stakeholder updates.
Liaise with broader technology team to advocate for Specialty Finance requirements and ensure solutions meet firm standards.
Work with investment stakeholders and convert them into clear technical specifications and prioritized roadmaps.
Identify high-impact AI opportunities
Required Qualifications
10+ years of relevant experience as a full-stack engineer specifically in specialty finance, asset-backed finance, private credit, or an adjacent buy-side setting.
Advanced Python skills for data engineering and analytics (pandas/numpy, API integration, scripting, testing).
Strong SQL skills and experience building analytics-ready data models with large data sets and hands-on Snowflake experience
Experience building dashboards and/or data applications (e.g., Streamlit/Dash, Plotly, Power BI/Tableau, or equivalent) with attention to UX for investment professionals.
Demonstrated project management ability: translating ambiguous needs into shipped products, managing stakeholders, and delivering on timelines.
Strong communication skills with the ability to work directly with investors and explain technical concepts clearly.
Requirements
Prior experience at a private credit / specialty finance buy-side firm, or direct exposure to loan-level consumer assets (mortgages, credit cards, ABS/RMBS, whole loans, or specialty lending).
Familiarity with core credit concepts and performance metrics (delinquency/default/loss, prepayment, seasoning, vintage/cohort tracking, credit enhancement/triggers, concentration and covenant monitoring).
Applied AI/ML experience (not necessarily deep research): using LLMs for workflow automation, document extraction, anomaly detection, or decision-support tooling.
Version Control & Delivery: Git, Microsoft Azure DevOps
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Applicants must be authorized and have the right to work in the country where the role is located without the need for current or future sponsorship.
Compensation Details
Note: No amount of pay is considered to be wages or compensation until s
Benefits
Dental insuranceVision insurancePerformance bonus
Additional Information
The Specialty Finance team is seeking a hands-on technical engineer to build and own a scalable analytics and dashboard platform that tracks deal performance across private credit and specialty finance asset classes. This person will partner closely with the Specialty Finance team and broader technology team to define requirements, build data pipelines and metrics for large data sets, and deliver a web-based portal where dashboards and analytical tools are centrally maintained. The role also includes an opportunity to lead pragmatic AI initiatives and elevate best practices in modern analytics and engineering.
You are a builder with a deep understanding of Specialty Finance who enjoys owning products end-to-end-data, analytics, and delivery. You can operate comfortably in an investment environment where requirements evolve, and you can balance speed with quality, controls, and maintainability.
Nb · Redwood, CA