Product Analytics Lead Brokerage

TheProduct Analytics Leadowns the end-to-end quantitative agenda forJPMorganPersonal Investing-Brokerage integrating advanced statistical methods machine learning and portfolio theory into production-grade solutionsand role designs and deploys propensity models to deepen client engagement builds portfolio construction frameworks grounded in Monte Carlo and optimization techniques and delivers rigorous business analytics for senior stakeholders.

Job responsibilities:

• Develop and enhance quantitative tools and reusable frameworks that support investment decision-making product development and ongoing performance monitoring.
• Own end-to-end business analytics for the Brokerage team transforming complex datasets into strategic insights and clearproductrecommendations for senior stakeholders.
• Conduct applied research on statistical machine learning and mathematical methods relevant to brokerage and personal investing use cases.
• Build andmaintainportfolio construction methodologies using Monte Carlo simulations optimization algorithms and risk models that align with clientobjectivesand guardrails.
• Lead the design development and deployment of propensity models and scoring frameworks that increase client acquisition activation cross-sell and retention.
• Partner with technology product and business teams to integrate models and analytics into production systems withappropriate scalability reliability and controls.
• Communicate findings trade-offs and recommendations with clarity and business context to leadership and cross-functional partners.

Required qualificationscapabilitiesand skills

• Advanced degree (Mastersor PhD) in Mathematics Statistics Physics Financial Engineering Computer Science or a related quantitative discipline.
• Significant experiencein quantitative analytics financial modelling or a related role within financial services with a demonstrated record of productionizing models.
• Strongproficiencyin Python and SQL including experience with scientific computing and machine learning libraries (NumPy SciPy pandas scikit-learn).
• Deepexpertisein statistical modelling probability theory Monte Carlo methods and optimization techniques.
• Experience building propensity models scoring systems or recommendation engines tied to measurable business outcomes.
• Ability to convey complex quantitative concepts to non-technical stakeholders with precision and brevity.
• Strong understanding of investment products portfolio theory and brokerage operations.
• Passion for investments with an entrepreneurial andbusiness orientedmindset.

Preferred qualificationscapabilitiesand skills

• Familiarity with cloud platforms (AWS GCP or Azure) for scalable data processing and model deployment.
• Knowledge of regulatory considerations relevant to brokerage and personal investing.
• Experience within model risk management or model governance frameworks.
• Prior experience in brokerage wealth management or asset management environments.
• Fluent in other European languages (beyond English)