Stealth is building an internal inventory economics and pricing decision platform designed to maximize cash recovery, improve margins, and optimize capital efficiency across aged, at-risk, and healthy inventory.
This role serves as the single-threaded owner of that platform.
You’ll sit at the intersection of pricing, inventory strategy, finance, data science, and engineering — translating ambiguity into structured, repeatable decisions that operate daily and materially impact financial outcomes. This is not purely an analytics or engineering role; it’s a product leadership role grounded in economics and decision systems.
What You’ll Do
- Own and continuously refine the economic logic behind pricing and inventory disposition (e.g., contribution margin, holding costs, option value).
- Define and evolve the framework for categorizing inventory (Bleeder / At-Risk / Healthy) along with the policies that govern each segment.
- Drive structured research and experimentation in ambiguous, low-signal environments.
- Partner closely with data science to shape time-to-sell, demand, and elasticity models — emphasizing interpretability and real-world usability.
- Leverage LLMs thoughtfully to accelerate hypothesis generation, feature ideation, matching, and model evaluation while maintaining strong guardrails.
- Work with engineering to productionize daily decision systems, including guardrails, monitoring, and override mechanisms.
- Build organizational trust through explainable recommendations, governance practices, and rigorous post-mortems.
- Apply formal reasoning where appropriate (constraints, invariants, verifiable logic) to ensure decisions are consistent, auditable, and correct.
What You Bring
- 8+ years of experience in pricing, inventory strategy, revenue management, marketplace economics, or applied data science within retail or e-commerce environments.
- Demonstrated ability to create clarity and forward momentum in highly ambiguous problem spaces.
- Strong intuition and rigor around unit economics and expected-value decision making.
- Experience influencing or owning systems that drive daily financial and operational decisions.
- Ability to collaborate effectively across data science, engineering, merchandising, and finance stakeholders.
Nice to Have
- Background in clearance, markdown optimization, or liquidation strategy.
- Familiarity with hazard modeling, demand forecasting, or experimentation frameworks.
- Hands-on experience incorporating LLMs into analytics workflows or decision systems.
- Exposure to formal logic, constraint-based systems, or verification-style reasoning.
