Principal Data Science & Analytics Consulting

Role Overview and Core Responsibilities
Strategic Leadership & Operating Model - Act as a co-leader and strategic advisor to DSA leadership. Drive multi-year strategy, including capability investment, portfolio prioritization, and operating model evolution. Own core business operations including revenue planning, capacity planning, resource allocation, and performance management.
Analytics & AI Consulting Leadership - Guide design and delivery of machine learning, statistical, and AI-driven solutions. Establish best practices for consulting processes including AI-enabled and platform-enabled consulting, model development, validation, and production deployment. Ensure scalable, high-quality analytics outcomes.
Product & Commercial Enablement - Partner with Solutions teams to define and commercialize new analytics products and platforms. Support client engagements, shape deals, and enable Sales through differentiated, data-driven narratives.
Cross-Functional Leadership - Operate effectively across a matrixed environment spanning Data Science, Technology, Solutions, and Sales. Drive alignment and end-to-end integration across data, models, platforms, and delivery.
Data & Platform Stewardship -Oversee development of high-value analytic data assets. Ensure strong governance across data quality, privacy, and regulatory compliance. Champion adoption of modern analytics tools and platforms.
Thought Leadership & Innovation - Contribute to intellectual property development including patents and proprietary methodologies. Maintain awareness of industry trends, emerging technologies, and competitive offerings. Deliver external-facing thought leadership.
Talent & Organizational Impact - Mentor senior talent, support recruiting strategy, and influence organizational culture. Drive adoption of best practices and improve productivity through process innovation.

Required Knowledge and Experiences
8+ years of experience in data science, analytics consulting, or related field in Financial Services or adjacent industries
5+ years in leadership roles with enterprise-level scope
Demonstrated ability to influence strategy, operations, and commercial outcomes
Deep expertise in machine learning, statistical modeling, and AI along with experience building and deploying production-grade model pipelines
Advanced degree (MS or PhD) in a quantitative discipline