Director, AI and Analytics

UFCU Plaza•Austin, TX

3d•Hybrid

About The Position

The Director, AI and Analytics is a collaborative, technical partner responsible for leading, architecting, and delivering UFCU’s portfolio of strategic, operational, and transformational AI solutions. This highly technical player-coach role combines hands-on work in designing, developing, training, deploying, and optimizing machine learning and generative AI solutions with leadership of the AI and Analytics team. The director partners across the organization to advance data usage, AI adoption, and predictive analytics, and to turn member insights into competitive advantages. The role reports to the VP, Data & AI and is an exempt position. The director develops and executes AI and analytics strategy aligned with business goals; leads end-to-end delivery of AI use cases into resilient production environments; and establishes technical standards, production practices, governance, and responsible AI practices. The position includes managing and mentoring multidisciplinary teams, partnering with executives and business and technology stakeholders, contributing to strategic planning, and overseeing budgets and resources. The role requires extensive Databricks experience and hands-on expertise developing and deploying enterprise machine learning models. The position is based at UFCU Plaza in Austin, Texas, and requires working there a minimum of two days each week. It may involve periodic stressful conditions, occasional schedule adjustments, overtime, and evening or weekend hours. The work includes frequent computer use at a workstation and extensive use of telephone and virtual communications.

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, and 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 build a high-performance climate through talent identification, recruitment, and retention.
Strong leadership skills and ability to inspire, motivate, and build teams with diverse, complementary talents.
High integrity and personal standards of behavior.
Exceptional interpersonal skills and ability to influence senior management and key stakeholders.
Effective communication, listening, and presentation skills with people at various organizational levels.
Ability to maintain effective relationships with internal departments, external business and community partners, and other stakeholders.
Proven delivery track record, service orientation, and ability to translate organizational mission into actionable, quantitative plans.
Ability to hold oneself and others accountable for individual and organizational performance.
Experience leading multidisciplinary technical teams and bringing complex products into production.
Hands-on experience with the Databricks ecosystem and a demonstrated history of personally developing and deploying machine learning models in enterprise production environments.
Expertise translating business goals into analytic objectives and solving problems creatively.
Ability to evaluate decisions in terms of business impact and communicate ideas to technical and non-technical audiences.
Extensive experience leading teams within Databricks Lakehouse architecture and deep familiarity with Spark (PySpark), Delta Lake, Unity Catalog, and MLflow.
Deep understanding of the full machine learning 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, including cluster management, workspace security, and environment automation.
Proficiency in Python, SQL, and Git.
Experience with automated testing, containerization, and orchestration tools in a cloud environment such as Azure or AWS.

Nice To Haves

Master’s degree in Data Science, Econometrics, Computer Science, or Operations Research.
At least five years of demonstrated strategic leadership experience.
Databricks Machine Learning Professional certification, Databricks Data Engineer Professional certification, 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 Databricks platform evolution, 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 relevant AI frameworks and technologies.
Drive implementation of LLM, RAG, agentic AI, and conversational AI solutions, establishing governance and responsible AI practices.
Conduct architecture and code reviews, provide technical mentoring, and serve as the technical escalation point for complex machine learning, model performance, and AI platform challenges.
Lead, motivate, develop, and coach team members; set goals, monitor performance, remove obstacles, and support employee career development.
Partner with executive leadership, business units, and technology stakeholders to identify high-impact AI and analytics opportunities and translate business needs into actionable roadmaps.
Collaborate across departments and with business partners to support operational results and future business-unit needs.
Develop AI and Analytics strategies with executive leadership, participate in organizational strategic planning, monitor progress toward goals, and adjust plans as needed.
Facilitate procurement of tools and resources needed for strategic priorities.
Establish the annual AI and Analytics budget, monitor expenses against budget, and take action to support departmental and organizational objectives.
Collaborate with senior leaders on the organizational annual budget.
Perform other duties as assigned and comply with organizational policies, regulatory training, laws, regulations, and role-specific internal controls.