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Director of Product Management – Financial Simulation & Modeling

sandboxaq

Senior 🇬🇧 English
risk modeling financial simulation portfolio analytics quantitative modeling

Description du poste

About the role

SandboxAQ is seeking a senior product leader to own the strategy and execution of its Finance & Risk Modeling portfolio within the AI Generation Engine (SAIGE) team. The Director will partner closely with financial services and insurance customers, engineering, research, and user‑research teams to translate complex quantitative problems into market‑ready AI products.

Key responsibilities

  • Define and drive the product vision, roadmap, and delivery for finance‑risk use cases such as portfolio risk, capital modeling, underwriting and analytics.
  • Lead rapid 0→1 prototyping, hypothesis testing and incubation of high‑potential AI and LQM solutions across multiple domains.
  • Collaborate with quantitative researchers, ML engineers and domain experts to shape clear product requirements and data needs.
  • Establish success metrics, validation strategies and compare approaches against existing risk‑management frameworks.
  • Build trusted relationships with senior customer stakeholders (heads of risk, CROs, actuaries) and guide them from discovery through pilot and adoption.
  • Communicate progress, learnings and recommendations to internal leadership and external partners.

Required profile

  • 10+ years of product management experience, including senior‑level (director/principal) responsibility for complex B2B or platform products.
  • Deep domain expertise in financial services or insurance risk modeling, financial simulation, portfolio analytics or related decision‑support tools.
  • Proven ability to work closely with quantitative and engineering teams to build AI/ML‑driven products.
  • Track record of taking ideas from concept through rapid prototyping to early‑stage product launch in ambiguous environments.

Required skills

  • Risk modeling and financial simulation.
  • Portfolio analytics and decision‑support tools.
  • AI/ML product development and quantitative modeling.
  • Translating technical model requirements into business value.

Questions fréquentes

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Source : ats:ashby

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