Quantitative Scientist, Forecasting & Demand Planning

Collectors is the leading creator of innovative technology that provides value-added services for collectors worldwide. We grade, authenticate, vault, and sell millions of record-setting collectibles, all while modernizing and digitalizing the process to further our mission of helping collectors pursue their passions. We’re always on the lookout for talented people to join our growing team. Our services span collectible trading cards, autographs, comic books, coins, video games, event tickets, and memorabilia. Our subsidiaries include PSA, PCGS, Beckett, SGC, and Card Ladder. Since our founding in 1986, we have graded and authenticated millions of items. We employ more than 3000 people across our headquarters in Santa Ana, California and offices in New Jersey, Texas, Florida, Japan, Shanghai, Hong Kong, Canada, Mexico, Germany, the UK, and France.

As part of our interview process, we request that candidates have their cameras on during video interviews. This helps foster meaningful conversation and allows us to create an experience that closely resembles our standard working environment. Certain interview steps may take place by phone. For remote roles, and at our discretion, candidates may be asked to participate in an on-site interview as part of the final stages of the process. We understand there may be occasional circumstances requiring accommodation and are happy to discuss them as needed. Your recruiter will be able to clarify expectations and answer any questions you have.

We're looking for a Quantitative Scientist, Forecasting & Demand Planning to help build the quantitative modeling capability at the core of Collectors' next phase of growth. This is unlike almost any other quantitative role in fintech or financial services. You'll be modeling asset classes — vintage sports cards, rare coins, sealed video games — where the data is uniquely ours, the domain expertise lives in-house, and the opportunity to build something from first principles is wide open. You'll join a small, early-stage team and work directly with its leader on modeling and infrastructure. We're looking for someone who wants to ship real models and grow quickly alongside the function.

What You’ll Do

• Modeling & Production: Leverage Collectors' proprietary grading, authentication, search and transaction data — one of the deepest datasets in the collectibles industry — as a core modeling advantage
  • Partner with Engineering to deploy models into production systems with appropriate monitoring, explainability, and feedback loops
  • Continuously improve model performance using new data sources, features, and methodologies
  • Partner with other members of the Product & Technology team to validate valuation models through rigorous backtesting and experimentation.
  • Collaborate with domain experts to improve feature engineering to ensure our models reflect the market nuances that drive sale prices
• Financial Forecasting: Build quantitative models that forecast market dynamics, asset valuations, and pricing trends across collectible categories (cards, coins, comics, banknotes, games, and beyond)
  • Develop and refine intelligence that supports and enhances our grading and authentication businesses
  • Generate insights that inform product, pricing, and go-to-market strategy across the Collectors portfolio
• Team & Collaboration: Join the Quantitative Sciences function as one of its first members, working directly with its leader
  • Contribute to the team's roadmap, research agenda, and technical standards
  • Collaborate cross-functionally with Product, Engineering, Finance, and Operations to understand business needs and turn them into well-scoped modeling work.

Who You Are

• 3–5 years of experience in quantitative finance, data science, machine learning, or a related field, with hands-on experience in pricing, demand forecasting, or asset valuation
• Solid ML fundamentals — you’ve built and validated supervised models on real data and have helped get at least one into production, not just in notebooks
• Strong Python and SQL — you’re fluent with the standard data stack (pandas, scikit-learn or similar) and comfortable working directly with large datasets
• Financial modeling foundations — you're familiar with concepts like time series forecasting, scenario analysis, and asset pricing
• Forecasting experience — you’ve built time series or demand forecasts and can produce scenario ranges (downside, base, upside), not just point estimates
• Production mindset — you care about model reliability, monitoring, drift detection, and working closely with engineering teams
• Comfort with ambiguity — you can make progress in a fast-moving environment and are comfortable working on problems with limited precedent
• Ownership and follow-through — you can take a loosely defined problem, scope it, and carry it to a shipped result with guidance from your lead
• Clear communication — you can explain your models and results to non-technical partners and back your recommendations with data
• Intellectual curiosity about alternative assets — you're excited (not intimidated) by the prospect of modeling asset classes that don't have decades of structured financial data behind them

Nice to Haves

• Experience in fintech or alternative/exotic asset valuation
• Advanced degree (MS/PhD) in a quantitative discipline — statistics, applied math, CS, physics, economics, operations research, or similar
• Exposure to demand planning or capacity planning in an operations-heavy business
• Personal interest in collectibles, trading cards, coins, or related hobbyist markets (not required, but it helps)

Why This Role

Proprietary data. Collectors has authenticated and graded hundreds of millions of collectibles. You'll build models on top of a dataset that simply doesn't exist anywhere else.

Early‑stage team. You'll join the Quantitative Sciences function near its start and help shape the models, the roadmap, and the culture.

Tangible business impact. The models you build will directly power how we price, plan capacity, and grow across a rapidly expanding market.

Category-defining work. Collectibles are becoming a recognized asset class. You'll help build the quantitative infrastructure that makes that possible.

Room to grow. You’ll work directly with the function’s leader, get hands‑on coaching, and take on more scope as the team and the models mature.

Compensation & Benefits

The estimated salary for this role is $187,400 - $253,500. Actual compensation may vary based on relevant experience, qualifications, geographic location, and other role-specific factors.

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Equal Employment Opportunity

We are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, national origin, gender, sex, gender identity or expression, sexual orientation, age, citizenship, marital or parental status, disability, veteran status, or other class protected by applicable law. We believe that a team that represents a variety of backgrounds, perspectives, and skills will better service the diverse community of collectors we support.

If you require an accommodation to apply or interview with us due to a disability or special need, please email View email address on click.appcast.io.

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Collectors is the leading creator of innovative technology that provides value-added services for collectors worldwide. We grade, authenticate, vault, and sell millions of record-setting collectibles, all while modernizing and digitalizing the process to further our mission of helping collectors pursue their passions. We’re always on the lookout for talented people to join our growing team. Our services span collectible trading cards, autographs, comic books, coins, video games, event tickets, and memorabilia. Our subsidiaries include PSA, PCGS, Beckett, SGC, and Card Ladder. Since our founding in 1986, we have graded and authenticated millions of items. We employ more than 3000 people across our headquarters in Santa Ana, California and offices in New Jersey, Texas, Florida, Japan, Shanghai, Hong Kong, Canada, Mexico, Germany, the UK, and France.