Corporate Finance - Data Science Product Associate

Join a team building modern data and analytics products that power Finance at scale. You'll partner with product, data science, and engineering to deliver user-centric capabilities that improve data quality and accelerate trusted reporting. Your work will shape model-powered features, intuitive dashboards, and controls that leaders rely on. Grow your impact through clear ownership, mentorship, and opportunities to drive change across high-visibility programs. Job Summary As a Data Science Product Associate in the Firmwide Finance Business Architecture Core Services Team, you transform complex business needs into analytics-driven features your users love. You collaborate with product managers, data scientists, and engineers to define requirements, acceptance criteria, and success metrics that tie directly to outcomes. You support development and testing of artificial intelligence and machine learning models and the controls that safeguard their use. You build executive-ready dashboards and narratives that inform decisions and prioritize the roadmap. You communicate clearly and inclusively, turning analytics into action for Finance controllers and reporting teams. You will help standardize reporting and playbooks that scale insights delivery across Finance, Treasury and the Chief Investment Office, and Wholesale Credit Risk platforms. You will strengthen data validation, lineage, and documentation, aligning to privacy, security, and model risk standards. You will facilitate cross-functional forums, synthesize feedback, and ensure analytics and controls are deployed reliably in strategic and legacy environments. Your work enables faster, more reliable close and reporting cycles while improving transparency and governance. Job Responsibilities

• Translate business problems into analytical requirements and clear acceptance criteria; refine epics and write user stories that maximize value.
• Analyze product usage, customer behavior, and model performance to surface insights that inform prioritization and roadmap decisions.
• Build executive-ready dashboards and narratives; design A/B tests and pilots, define success metrics, and evaluate outcomes including return on investment.
• Partner with engineering on data validation, lineage, documentation, and control alignment; ensure compliance with privacy, security, and model risk requirements.
• Maintain and prioritize a backlog of data enhancements aligned to business outcomes; manage delivery using Agile practices and tooling.
• Facilitate cross-functional forums; synthesize feedback into clear recommendations and communicate complex findings in business language.
• Standardize reporting, create playbooks, and streamline processes for repeatable, scalable insights delivery.
• Support development and testing of AI and machine learning models and data controls to improve data quality and operational efficiency.

Required Qualifications, Capabilities, and Skills...