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4 mo agofound 7 d ago

Staff Data Scientist, Pricing

Courtyard.io·United States·via greenhouse
staff5+ yrsFull timepythonsql
What the posting is about

Own and evolve pricing models for diverse collectibles. Build data quality and anomaly detection systems. Collaborate with cross-functional teams to drive pricing decisions. Requires strong statistical background and experience with sparse, irregular data. Offers competitive salary, health insurance, 401(k), and remote work.

Read out of the posting
Levelstaff
Experience asked5+ years
EmploymentFull time
LocationUnited States
RemoteNot stated
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2026-05-15
Found viagreenhouse, direct from their system

We saw it 5 months after it went up.

The posting, as the company wrote it
About Courtyard Courtyard.io is the fastest-growing collectibles startup, ever. We are revolutionizing the world of collectibles trading by enabling instant liquidity and delivering a high-velocity, immersive experience. From trading cards to comics, we’re redefining how people discover, collect, and unlock value. Courtyard is not just another marketplace. All assets are securely vaulted and fully insured, giving collectors peace of mind alongside unmatched speed and simplicity. Whether you’re investing, discovering, or curating your dream collection, we’ve built a platform that’s trusted, simple, and built for speed. And we’re just getting started. We’re a remote-first company hiring across all functions to push the boundaries of what’s possible in collectibles and digital ownership. Job Summary Courtyard is hiring a Staff Data Scientist to own pricing across our portfolio collectibles. Pricing is load-bearing at our business — it touches revenue and operational decisions daily, with direct financial consequences. This role builds and improves our pricing methodology across a large, heterogeneous catalog of often-thinly-traded assets.You'll partner closely with engineering on our pricing pipeline, with operations on real-world feedback loops, and with the rest of the data team on measurement and evaluation. What You’ll Do Own and evolve pricing models across asset categories, including designing approaches for new and sparsely-traded asset types Build data quality and anomaly detection systems for adversarial and corrupted external data inputs Ship production code into our pricing pipeline and services in partnership with engineering Partner with operations, finance, and product on pricing-related decisions across the company What We’re Looking For Strong foundations in applied statistics, economics, or signal processing — robust estimation, state-space models, sparse/hierarchical data, anomaly detection, and uncertainty quantification Backgrounds of interest: quantitative trading, fraud/anomaly detection, computational neuroscience or physics — in addition to traditional pricing or marketplace DS Track record owning a production scoring or pricing system end-to-end Production-grade Python and SQL; comfort working inside a real codebase and shipping models into continuously-running services Experience with sparse, irregular, heterogeneous, or adversarial data Pragmatism about modeling — right tool for the data you actually have 5+ years of industry experience or Ph.d Bonus: experience sourcing heterogeneous external data via API or scraping What You’ll Get In Return A dynamic and engaging environment focused on fostering real growth and innovation Opportunities to create amazing products that our customers truly love and value Comprehensive health insurance packages with dependent coverage Competitive salary with ample opportunities for career advancement and development Enjoy the flexibility of a fully remote work environment 401(k) plan with a 4% employer match to help you plan for the future $100 monthly dogfooding stipend to support trying out our products firsthand Access to employee wellness programs designed to support your overall well-being

Copied from Courtyard.io’s own board, not rewritten. Original ↗

Also open at Courtyard.io

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