Head of Data and AI

The Minnesota Star Tribune•Fridley, MN

17h•$137,300 - $225,000•Hybrid

About The Position

The Head of Data and AI at the Minnesota Star Tribune leads the enterprise data and artificial intelligence function. This role is accountable for the data platform, the Custom AI team, and the governance surrounding both. The position reports to the Chief Product and Technology Officer and manages the data and AI team across data engineering, analytics, and applied AI. The Head of Data and AI owns the function's technology and vendor budget, and sets long-term data architecture, technology stack, and standard operating procedures for the entire corporation. This role also owns enterprise-wide AI accountability and strategic alignment, applying AI principles to AI Accelerator efforts across all departments. It involves establishing governance standards and partnering with Legal, Editorial, and Product and Technology on responsible AI governance and the handling of sensitive data. The company's platform spans Next.js, NestJS, Apollo GraphQL with Stellate, AWS, Vercel, Snowflake, Domo, Piano, Sailthru, Datadog, VictorOps, GitHub, Slack, and Jira.

Requirements

Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or related technical field; advanced degree preferred.
Minimum of 10 years of experience in data, analytics, AI, or machine learning, including a minimum of 3 years in leadership roles.
Deep expertise in enterprise data architecture, modern data platforms, Snowflake, data modeling, cost governance, and transformation frameworks such as dbt.
Proven experience building and leading AI/ML functions and scaling solutions from prototype to enterprise production environments.
Strong knowledge of AI governance, responsible AI practices, bias mitigation, risk management, and handling sensitive data.
Experience with data privacy, compliance reporting, data security controls, and incident response management.
Hands-on experience developing recommendation engines, personalization systems, predictive models, or subscriber/customer intelligence solutions.
Practitioner-level expertise with AI-powered tools and agentic workflows (e.g., ChatGPT, Claude, Copilot, Cursor, AI agents).
Strong business acumen with experience managing budgets, vendor relationships, and aligning technology investments with organizational goals.
Excellent communication and executive-level stakeholder management skills, with the ability to influence both technical and non-technical audiences.
Demonstrated success leading teams, developing talent, and driving organizational change and technology adoption.
Must be currently legally authorized to work in the U.S. without sponsorship for employment visa status (e.g., H1B status, 0-1, TM, CPT, OPT, etc.). We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Nice To Haves

Experience within media, publishing, subscription, or consumer-focused businesses preferred.
Experience partnering with Legal, Editorial, Product, Revenue, and Technology stakeholders preferred.

Responsibilities

Lead enterprise data architecture, platform strategy, and modernization initiatives, including Snowflake, dbt, and AI/data technology frameworks.
Ensure data platform reliability, governance, performance, and cost management, including pipeline operations, incident response, and budget oversight.
Lead the development and deployment of custom AI solutions and establish standards for production AI, including model governance, deployment, monitoring, and ownership.
Develop and maintain the enterprise AI roadmap, ensuring alignment across Product, Technology, and business functions.
Establish and oversee AI governance frameworks, responsible AI practices, bias mitigation, risk management, and compliance for sensitive data usage.
Create and manage data governance programs, including data stewardship, quality standards, lineage, retention policies, and Data as a Product initiatives.
Partner with Legal, Editorial, Product, Engineering, and IT teams to ensure compliance, data security, and enterprise AI accountability.
Lead data security efforts, access controls, incident response, and remediation processes related to sensitive data exposures.
Manage, mentor, and grow data and AI teams, including hiring, performance management, workforce planning, and employee development.
Drive AI adoption across the organization through training, change management, and enablement programs.
Build and optimize AI-driven personalization, recommendation, and subscriber intelligence solutions to improve engagement, retention, and business outcomes.
Monitor and balance AI model performance, operational costs, fairness, and bias mitigation across production systems.