Senior Vice President, Data & AI Governance and Tooling Lead

LPL FinancialFort Mill, SC, US

30+ days ago

Job type

Full-time

Job description

Senior Vice President Of Data & Ai Governance And Tooling

LPL Financial (Nasdaq : LPLA) was founded on the principle that the firm should work for the advisor, and not the other way around. LPL Financial is one of the nation's leading financial services companies and a publicly traded company under ticker symbol LPLA. LPL is a fast-growing, fortune 500 company with 7000+ employees. We support over 50,000 financial professionalsincluding over 20,000 independent advisor teams, more than 800 financial institutions, and over 4,000 institutional clearing and technology subscribers managing over USD 1.2 trillion in assets.

At LPL, independence means that advisors have the freedom they deserve to choose the business model, services, and technology resources that allow them to run their perfect practice. And they have the freedom to manage their client relationships because they know their clients best. Simply put, we take care of our advisors, so they can take care of their clients.

This role offers a unique opportunity to shape the future of LPL Financials' data governance and contribute to the organization's strategic goals.

Overview

The Senior Vice President of Data & AI Governance and Tooling will lead the development and execution of enterprise-wide governance strategies for both data and AI. This role supports LPL's evolution into a hybrid "build and buy" AI organization by ensuring governance is embedded across data assets, AI models, and operational workflows.

Reporting to the Chief Data & AI Officer, this leader will scale governance capabilitiesincluding data cataloging, quality, lineage, reconciliation, and documentationwhile also establishing robust AI governance frameworks. The role requires close collaboration with data, technology, operations, legal, and compliance teams to align governance with business goals and regulatory expectations.

This leader will also drive adoption of governance tools, foster data curiosity, and ensure teams are equipped to use governance dashboards and insights to support decision-making and innovation.

Key Responsibilities

AI Governance : Define and manage governance for AI / ML and GenAI models, covering lifecycle oversight, risk, explainability, bias, and performance.
Policy Leadership : Develop and enforce enterprise-wide data and AI policies, including Partial Data Masking and Data Retention, integrated into platforms and workflows (e.g., ServiceNow).
Regulatory Alignment : Ensure governance practices meet or exceed FINRA and other regulatory standards; proactively adapt to changes.
Tooling Strategy : Expand use of AI-driven tools for metadata tagging, lineage, documentation, and reconciliation.
Governance Reporting : Build dashboards and metrics to track AI model governance, policy compliance, and audit readiness.
Cross-Functional Collaboration : Partner with engineering, data science, legal, and compliance to embed governance into development and operations.
Data Governance Delivery : Scale core capabilitiescataloging, quality, lineage, reconciliation, and documentationusing a mix of build, buy, and AI solutions.
Change Management : Lead adoption strategies and training to embed governance into daily workflows across teams.
Team Leadership : Mentor and grow a high-performing team of data professionals.
Continuous Improvement : Refine governance practices based on feedback, performance data, and industry trends.

Kpis & Success Metrics

AI Governance

% of AI models reviewed and approved through governance processes

% of models with explainability and bias assessments completed

Policy Compliance

% compliance with data retention and masking policies

Reduction in regulatory audit findings related to data / AI governance

Tooling Adoption & Data Quality

% of business units actively using governance tools (catalog, lineage, reconciliation)

Reduction in critical data quality issues over time

% of assets with complete and current metadata

Operational Efficiency

Mean time to resolve data-related incidents (via ServiceNow)

% of critical data domains governed

Training & Enablement

Number of users trained

Satisfaction scores from enablement sessions

Key Competencies

Data Governance : Expert in data governance, specifically cataloging, quality, lineage, reconciliation, and documentation of data assets.

AI Risk & Ethics : Deep understanding of responsible AI principles and regulatory trends.

Policy Leadership : Proven ability to develop and enforce enterprise-wide data and AI policies.

Regulatory Acumen : Familiarity with financial services regulations, especially those impacting data privacy, security, and AI usage.

Strategic Thinking : The ability to develop and implement long-term strategies that align with organizational goals.

Adaptability : The flexibility to adapt strategies and approaches based on changing circumstances and emerging trends.

Collaboration : Strong collaborative skills to work effectively with cross-functional teams and stakeholders.

Leadership : The ability to inspire, motivate, and develop team members to achieve high performance.

Communication : Clear and effective communication skills, both written and verbal.

Requirements

A bachelor's or master's degree in business, Computer Science, Information Systems, Data Science, Engineering, or a related field.

At least 15 or more years of experience in Data & Analytics product management or equivalent experience, including a proven track record of leading significant successful data transformation initiatives in complex environments.

Minimum 5 or more years of experience in data platform and services build-out in partnership with engineering teams and data product ownership in a mid to large scale enterprise.

Proven experience in a senior leadership role, preferably at the SVP level.

Strong financial acumen with a track record of effectively managing budgets exceeding $50 million.

Experience leading teams through significant transformations, particularly in migrating from legacy systems to modern cloud architectures.

Exceptional communication and stakeholder management skills.

Demonstrated ability to foster a collaborative and innovative team culture.

Experience with DataZone from AWS a plus

Pay Range : $179,775-$299,625 / year Actual base salary varies based on factors, including but not limited to, relevant skill, prior experience, education, base salary of internal peers, demonstrated performance, and geographic location. Additionally, LPL Total Rewards package is highly competitive, designed to support your success at work, at home, and at play such as 401K matching, health benefits, employee stock options, paid time off, volunteer time off, and more. Your recruiter will be happy to discuss all that LPL has to offer!

LPL Financial Holdings Inc. (Nasdaq : LPLA) was founded on the principle that the firm should work for advisors and institutions, and not the other way around. Today, LPL is a leader in the markets we serve, serving more than 23,000 financial advisors, including advisors at approximately 1,000 institutions and at approximately 580 registered investment advisor ("RIA") firms nationwide. We are steadfast in our commitment to the advisor-mediated model and the belief that Americans deserve access to personalized guidance from a financial professional.

At LPL, independence means that advisors and institution leaders have the freedom they deserve to choose the business model, services, and technology resources that allow them to run a thriving business. They have the flexibility to do business their way. And they have the freedom to manage their client relationships, because they know their clients best. Simply put, we take care of our advisors and institutions, so they can take care of their clients.

Join LPL Financial : Where Your Potential Meets Opportunity

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Senior Vice President • Fort Mill, SC, US