Director, AI and Analytics

UFCU•Austin, TX

4d•Hybrid

About The Position

The Director, AI & Analytics is a collaborative, technical player-coach who leads, architects, and delivers UFCU’s strategic, operational, and transformational AI solutions. The role advances enterprise data usage, AI adoption, and predictive analytics, with hands-on involvement in designing, developing, training, deploying, and optimizing machine learning and generative AI solutions. The Director leads the AI & Analytics team and reports to the VP, Data & AI. The Director develops and executes AI and analytics strategy aligned with business goals, takes AI use cases from experimentation into resilient production, and establishes technical standards and production practices. The role partners with executive leadership, business units, and technology stakeholders to translate business needs into technical roadmaps and prioritize work based on business value and ROI. It leads model development and implementation of machine learning, LLM, RAG, agentic AI, and conversational AI solutions, while establishing governance and responsible AI practices. The position also leads and develops multidisciplinary teams, contributes to organizational strategic planning, oversees the department’s budget and expenses, and ensures compliance with applicable organizational policies, laws, regulations, and internal controls. The position is based at UFCU Plaza in Austin, Texas, with a requirement to work there at least two days each week. Periodic stressful conditions and occasional schedule adjustments, overtime, and evening or weekend hours may be involved.

Requirements

Bachelor’s degree in Data Science, Econometrics, Computer Science, Operations Research, or a relevant field, or equivalent experience.
At least 10 years of related experience in Data Science, AI & Analytics.
At least 7 years of management and supervisory leadership experience developing and leading teams with direct reporting relationships.
Experience developing predictive models, recommendation engines, customer segmentation models, risk models, fraud detection models, and generative AI applications.
Experience managing multiple teams across AI, data science, and analytics delivery.
Experience working in a credit union or financial services industry.
Extensive experience with modern data science platforms; Databricks is preferred.
Must be bondable.
Proven ability to create a high-performance climate through talent identification, recruitment, and retention; build diverse teams; inspire and motivate others; and demonstrate integrity.
Strong interpersonal, communication, listening, presentation, relationship-building, and influencing skills, including the ability to work with senior management and stakeholders.
A proven delivery track record, service orientation, persistence, accountability, and ability to translate organizational mission into actionable, quantitative plans.
Hands-on experience leading teams using Databricks Lakehouse architecture, with deep familiarity with Spark (PySpark), Delta Lake, Unity Catalog, and MLflow.
Deep understanding of the ML lifecycle, including data engineering and wrangling, feature engineering, model training, real-time and batch deployment, and model drift monitoring.
Ability to influence IT and Platform Engineering teams on infrastructure needs such as cluster management, workspace security, and environment automation.
Proficiency in Python, SQL, and Git, and experience with automated testing, containerization, and orchestration tools in a cloud environment such as Azure or AWS.
Demonstrated history of personally developing and deploying machine learning models in enterprise production environments.
Ability to translate business goals into analytic objectives, solve problems creatively, evaluate decisions for business impact, and communicate with technical and non-technical audiences.
Combination of technical knowledge, business acumen, and organizational leadership skills.

Nice To Haves

Master’s degree in Data Science, Econometrics, Computer Science, or Operations Research.
At least 5 years of demonstrated strategic leadership experience.
Certifications such as Databricks Machine Learning Professional, Databricks Data Engineer Professional, or a cloud architect certification (Azure, AWS, or GCP), or equivalent.

Responsibilities

Lead end-to-end delivery of AI use cases, moving them from experimentation into resilient production environments.
Define technical standards for AI delivery and influence IT and Data Engineering teams on the Databricks platform, Unity Catalog, and feature store requirements.
Manage and mentor teams across data science, machine learning engineering, and operational business analytics.
Translate executive business goals into technical execution and prioritize the AI roadmap based on business value and ROI.
Establish CI/CD, MLOps, and model monitoring standards in the Databricks environment.
Develop and execute the organization’s AI and analytics strategy in alignment with business goals.
Lead model development, including feature engineering, model selection, hyperparameter tuning, validation, and performance optimization.
Build and review Python-based machine learning solutions using technologies such as MLflow, PyTorch, TensorFlow, Scikit-learn, and LangChain.
Drive implementation of LLM, RAG, agentic AI, and conversational AI solutions and establish governance and responsible AI practices.
Conduct architecture reviews and code reviews, provide technical mentoring, and serve as the escalation point for complex machine learning, model performance, and AI platform challenges.
Guide, train, coach, and develop team members; monitor performance and help employees achieve development and career goals.
Build a successful team aligned with UFCU’s guiding principles, provide resources, remove obstacles, and lead according to servant leadership principles.
Partner with executive leadership, business units, and technology stakeholders to identify high-impact AI and analytics opportunities and translate business needs into data and technology roadmaps.
Build collaborative relationships across the organization and work with business partners to support operational results and future business needs.
Participate in organizational strategic planning and develop AI and analytics strategies with executive leadership.
Monitor departmental progress toward goals and adjust plans as needed.
Facilitate procurement of tools and resources needed for organizational and departmental strategic priorities.
Establish the annual AI & Analytics budget, plan expenses, monitor spending, and take action to achieve objectives within budget.
Collaborate with senior leaders on the organizational annual budget.
Perform other duties as assigned and comply with organizational policies, business ethics codes, required regulatory training, and applicable laws, regulations, and internal controls, including BSA, AML, USA Patriot Act, OFAC, and Fair Lending requirements.