Lead Quantitative Scientist

Company Overview Collectors is a leading creator of innovative technology that modernizes and digitalizes the collectible marketplace, offering graded, authenticated, and traded items worldwide. Location & Work Arrangement Work will be based from our Santa Ana, CA or Jersey City, NJ offices. Remote or hybrid candidates may be considered, but if you live within an hour commute of an office you will be required to be onsite most of the time. What You’ll Do Design, build, and iterate on ML and quantitative models powering automated underwriting for collectible‑backed lending. Develop collateral valuation, credit risk, loss‑forecasting, and pricing models that scale reliably. Leverage our proprietary grading, authentication, search, and transaction data as a core modeling advantage. Partner with Engineering to deploy models into production systems with monitoring, explainability, and feedback loops. Continuously improve model performance using new data sources, features, and methodologies. Validate valuation models through rigorous back‑testing and experimentation with Product & Technology teams. Collaborate with domain experts to refine feature engineering so models capture market nuances of sale prices. Build quantitative models forecasting market dynamics, asset valuations, and pricing trends across card, coin, comic, banknote, game, and other collectible categories. Develop intelligence supporting PSA, Beckett, PCGS, and other grading and authentication businesses. Generate insights that inform product, pricing, and go‑to‑market strategy across the Collectors portfolio. Define the Quantitative Sciences function’s roadmap, research agenda, and technical standards. Translate business needs into modeling priorities in collaboration with Product, Engineering, Finance, and Risk. Who You Are 10+ years of experience in quantitative finance, data science, machine learning, or a related field, with depth in credit/lending, pricing, risk modeling, or asset valuation. Strong ML fundamentals; have built, validated, and deployed supervised or unsupervised models in production. Financial modeling fluency with concepts such as probability of default, loss given default, expected loss, time‑series forecasting, and asset pricing. Production mindset: care about reliability, monitoring, drift detection, and collaboration with engineering. Entrepreneurial orientation: thrive in ambiguous, fast‑moving environments and own problems end‑to‑end. Emerging leadership skills: have mentored others, led projects, and are eager to grow into a people‑leadership role. Strong communication skills: translate complex quantitative concepts for non‑technical stakeholders. Intellectual curiosity about alternative assets and pleasure in modeling classes with limited historic data. Nice to Have Experience in fintech, marketplace lending, or alternative/exotic asset valuation. Advanced degree (MS/PhD) in a quantitative discipline (statistics, applied math, CS, physics, economics, operations research, or similar). Experience building underwriting or credit decisioning systems from scratch. Familiarity with alternative data sources and feature engineering for non‑traditional collateral or thin‑file credit assessment. Personal interest in collectibles, trading cards, coins, or related hobbyist markets. Salary Salary range: $235,347–$331,754, with additional compensation such as bonuses or commissions as applicable. Benefits Health, Dental, and Vision insurance. Fertility, commuter, and educational assistance. 401(k) matching plan. Flexible time‑off and ten company paid holidays. Employee discounts on grading services. Flexible hours. Team building activities and holiday events. Equal Employment Opportunity We are committed to equal employment opportunity for all applicants regardless of race, color, ethnicity, religion, gender, sexual orientation, age, citizenship, disability, veteran status, or other protected characteristic. Accommodations are available for disabled applicants. Fraud Prevention We never ask for personal information such as bank account, social security number, or identity numbers, nor do we request payments for business‑related equipment. If you suspect fraud, contact View email address on click.appcast.io. #J-18808-Ljbffr Collectors Universe