Data Quality Associate Jobs in Milwaukee, WI (NOW HIRING)

At Landmark Credit Union, we succeed by putting people first - and that starts with you. Our culture of inclusion and collaboration enables us to support our members’ financial wellbeing, positively impact the communities we serve, and help our associates grow their careers. Bring your authentic self to work as part of an organization where you’ll feel valued for your unique qualities, are enabled to reach your full potential, and are recognized for your contributions to our success. We strive to ensure you feel empowered to grow and succeed, while also feeling valued and taken care of, as we all do our part to put people first. We invite you to learn more about this and other opportunities at Landmark Credit Union.

NATURE AND SCOPE:
The VP, Analytics and AI is responsible for defining and executing Landmark Credit Union’s enterprise data, analytics, and artificial intelligence strategy to improve member experience, operational efficiency, business decision-making, and risk management. This position leads the development of modern data and analytics capabilities, including business intelligence, advanced analytics, machine learning, automation, and responsible AI practices. The VP, Analytics and AI partners closely with IT, Digital, Lending, Finance, Risk, Marketing, Operations, and other business leaders to identify high-value opportunities, deliver actionable insights, and ensure data and AI investments support enterprise strategy, regulatory expectations, and measurable business outcomes. This role reports to the Chief Technology Officer and leads the Enterprise Analytics and AI function, including BI/reporting, data science, and AI/automation teams.

REQUIREMENTS:

1. Bachelor’s degree required in a quantitative, technical, or related field such as Data Science, Computer Science, Statistics, Mathematics, Economics, Information Systems, or a comparable discipline; advanced degree preferred.
2. A minimum of 10 years of progressive experience in analytics, data science, business intelligence, data leadership, or related roles, including several years leading enterprise-level teams and capabilities.
3. Proven experience defining and executing enterprise data, analytics, and AI strategies that deliver measurable business outcomes, preferably within a regulated industry such as financial services.
4. Strong understanding of data modeling, analytics techniques, machine learning concepts, modern data platforms, data pipelines, business intelligence tools, and AI-enabled solutions.
5. Hands-on familiarity with modern data and AI tools and technologies, including SQL, Python or R, cloud data platforms, and BI tools such as Power BI or Tableau.
6. Experience establishing data governance, data quality, privacy, security, model governance, and responsible AI practices in partnership with Risk, Compliance, Audit, Information Security, and business stakeholders.
7. Demonstrated ability to build, lead, develop, and retain high-performing analytics, BI, data science, and AI teams.
8. Strong executive communication, stakeholder management, and change leadership skills, including the ability to present complex data, analytics, AI, value realization, risk considerations, and investment needs to executive leadership and the Board.
9. Must develop a thorough understanding of company policies and procedures as they relate to this position. Must understand and comply with all job-related State and Federal laws and regulations.
   

PRINCIPAL ACCOUNTABILITIES:

1. Define and execute a multi-year enterprise analytics and AI roadmap aligned to organizational strategy, digital transformation objectives, and regulatory expectations.
2. Identify, evaluate, and prioritize high-impact analytics and AI use cases across member engagement, pricing, fraud and risk management, operations automation, marketing personalization, and other enterprise opportunities.
3. Partner with IT leadership to design, evolve, and govern modern data platforms, including data lake, data warehouse, real-time data pipelines, business intelligence tools, and self-service analytics capabilities.
4. Establish, own, and mature enterprise data governance policies, data quality standards, stewardship practices, and controls that support privacy, security, compliance, and trusted data usage.
5. Lead teams responsible for business intelligence, reporting, advanced analytics, data science, AI, and automation, ensuring delivery of actionable insights and decision-support tools for executives, business leaders, and frontline managers.
6. Oversee the development of dashboards, models, analytics products, and recommendations that translate complex data into clear narratives, business insights, and measurable actions.
7. Build and scale AI and automation capabilities, such as recommendation engines, intelligent routing, chatbots, document processing, claims processing, and marketing personalization, to enhance member experience and operational efficiency.
8. Define and enforce responsible AI practices, including model governance, model monitoring, bias management, explainability, human-in-the-loop controls, and appropriate collaboration with Risk and Compliance.
9. Serve as the primary analytics and AI partner to leaders across Lending, Retail, Digital, Marketing, Finance, Risk, Operations, and other business areas, helping teams use data and AI to drive better decisions and outcomes.
10. Communicate analytics and AI strategy, priorities, results, risks, investment needs, and value realization clearly to leadership and governance forums.
11. Build and lead high-performing analytics, BI, data science, and AI organizations; attract, develop, coach, and retain talent capable of supporting enterprise needs.
12. Foster a culture of data-driven decision-making, innovation, responsible experimentation, and practical adoption of data and AI across the organization.
13. Define KPIs and success measures for analytics and AI initiatives and regularly measure and report business impact, including member growth, member experience, efficiency gains, risk reduction, and financial value.
14. Manage analytics and AI budgets, platforms, tools, vendors, staffing plans, and portfolio priorities to ensure investments deliver measurable value.
15. Perform other duties as assigned.