The Role

As a Pricing Data Scientist, you will be the architect of the logic behind the Alt Value, Alt’s core pricing model. You will research, design, and validate the science and models that will price millions of alternative assets in real-time. This role is highly collaborative; you will work alongside Expert Pricers to translate human intuition into mathematical features and partner with Data and ML Engineers to bring those models to life at scale.

What you'll do here

• Research, develop, and ship sophisticated pricing models (e.g. Tree-based, Gradient-based, Deep Learning, ensemble methods) to improve valuation accuracy for high-value assets.
• Identify new data signals — emanating from data such as auction results to social sentiment — and validate their predictive power through rigorous backtesting and experimentation.
• Partner with the Product Engineering team to refine our Risk & Underwriting models, balancing the goal of maximizing cash advances with the need to maintain a balanced lending portfolio.
• Collaborate with the Expert Pricing team and domain experts to encode market nuances into automated features and inferences, ensuring our models respect the qualitative factors collectors care about.
• Define, monitor, and lift model performance metrics and communicate the "why" behind price coverage, movements, and freshness toward becoming the ultimate liquidity platform.

This is a perfect fit if you...

• Are deeply curious about how value is assigned to unique, non-traditional, and conventionally “illiquid” asset classes.
• Are a hands-on individual contributor who thrives in a zero-to-one startup environment.
• Are a product-minded builder who wants to see their work deployed in a user-facing production application.

What you bring to the table

• 5+ years of experience in Data Science, with a focus on feature engineering and algorithm/model-building in the pricing, financial modeling, or marketplace dynamics domains.
• Expert-level proficiency in SQL, Python, and populate Python libraries (Pandas, Scikit-Learn, XGBoost/LightGBM, PyTorch/Tensforflow).
• Statistical rigor and deep understanding of experimental design, backtesting methodologies, and dealing with "noisy" or sparse data environments.
• Collaborative experience working in a sprint-based environment alongside Data and ML Engineers; you understand enough about model hand-offs and quality code to ensure your models are efficient and readily "production-capable".
• Proficient in developing in cloud environments (AWS, GCP) and familiarity with ML Ops infrastructure (e.g. MLFlow, workflow and container orchestration, deployment and telemetry patterns).
• Advanced degree (Master’s or PhD) in a quantitative field such as Statistics, Economics, Mathematics, or Computer Science is preferred.

Compensation: $200,000

What You’ll Get From Us

• A seat at the table to help shape the future of Alt and the alternative asset space
• Autonomy and ownership on projects that matter
• $100/month work-from-home stipend
• $200/month wellness stipend
• WeWork office stipend
• 401(k) retirement benefits
• Flexible vacation policy
• Generous paid parental leave
• Competitive healthcare benefits, including HSA, for you and your dependent(s)