Drive innovation in Investment Banking by designing, building, and scaling data products and pipelines for analytics and AI/ML.

As an Investment Banking Data & Analytics Vice President, you will play a hands-on, product-oriented role in converting domain needs into governed, reliable data assets with clear contracts, SLAs, and measurable outcomes. You will partner across business, technology, and platform teams to deliver actionable insights via APIs, marts, dashboards, and notebooks, enabling advanced analytics and AI/ML capabilities.

Key Responsibilities

• Own a portfolio of IB data products: vision, backlog, roadmap, releases; define data contracts, quality SLAs, and operating KPIs.
• Build and operate batch/streaming pipelines using platform capabilities; enforce schema management, testing, observability, and cost/performance optimization.
• Enable AI/ML: provision features and labeled datasets via feature stores and governed marts; integrate with MLOps
• Deliver data products and insights through consumption channels (APIs/data services, SQL endpoints, dashboards, notebooks); design domain semantic layers for common IB analytics.
• Apply governance and controls: stewardship, cataloging, lineage, entitlements; protect sensitive data with masking/tokenization/entitlements and regulatory compliance.
• Engage stakeholders to prioritize use cases and communicate outcomes; partner with architecture/platform teams to leverage strategic capabilities.
• Provide technical leadership and mentorship (code reviews, delivery standards, continuous improvement).

Required Qualifications

• Bachelor’s in computer science, Data Science, Engineering, Finance; advanced degree a plus.
• 8+ years in data engineering and/or data product development in financial services with production delivery.
• Proficiency: Product Thinking; Experience with Databricks/Snowflake; Data Products Buildout
• Strong grasp of data governance, quality, compliance; experience enabling AI/ML workloads.
• Familiarity with IB domains (deal lifecycle, client coverage, pipeline/execution, fee/revenue analytics).
• Excellent communication; outcome-focused and hands-on.

Preferred Qualifications

• Domain-driven models and semantic layers; lakehouse formats (Delta/Iceberg); data observability.
• Data mesh/product thinking; privacy-enhancing techniques.

Why Join Us

• Build data products that materially improve IB decision-making.
• Work at the intersection of business, data, and AI/ML with clear ownership and impact.
• Competitive compensation and benefits.