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Overall Responsibility

The primary purpose of this role is to design, develop, and operationalize AI/ML solutions and semantic data models that enable advanced analytics for the credit union. This individual will work with channel leads, data stewards, and business stakeholders to interpret requirements, create scalable data pipelines, build semantic layers in Snowflake, and develop AI/ML models using Python and SQL. The role also involves integrating models into Tableau dashboards, ensuring data quality, and aligning with governance standards to support actionable and responsible AI adoption.

Essential Functions

• Design, build, and optimize semantic models in Snowflake to support advanced analytics and AI-driven insights.
• Develop and maintain ML pipelines using Python, Snowflake, and SQL for credit union business use cases.
• Analyze and extract/transform data from multiple sources to create new data tables/sources for semantic layers and model training.
• Collaborate with business stakeholders to translate requirements into AI/ML models and data products.
• Enhance and integrate Tableau dashboards with predictive/AI models to deliver actionable insights.
• Apply data governance practices to ensure data quality, lineage, and compliance with regulations.
• Document methodologies, processes, and model decisions to enable transparency and reproducibility.
• Present technical findings and AI-driven insights to diverse stakeholders, bridging technical and business perspectives.
• Work in an Agile environment, handle deliverables assigned in a sprint, work with JIRA to update stories, and participate in agile rituals like sprint planning, backlog grooming, and sprint retrospectives.
• Ability to work independently and within a collaborative team environment and communicate effectively to technical and non-technical audiences.
• Other duties as assigned. 

POSITION REQUIREMENTS: 

 Minimum Education/Experience:   Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related      field is required plus a minimum of four (4) years of experience in the specific or related field; or High School Diploma or equivalent plus a minimum of eight (8) years of experience in the field.    

 Company / Industry Knowledge:   Prior experience in a field related to Consumer Banking products (auto loans, personal loans, student loans, credit cards) is preferred.

Other Skills & Abilities:

• Minimum of four (4) years of total experience in data engineering, or advanced analytics and 1 year in AI/ML engineering.
• Experience in a field related to Consumer Banking products (auto loans, personal loans, student loans, credit cards) is preferred.
• Hands-on skills in Snowflake, Python, SQL, and Tableau (Desktop & Prep) are required.
• Experience with semantic layers, AI-to-SQL techniques, and LLM-based approaches is highly preferred.
• Experience with Ataccama/Collibra or any data governance tool highly preferred.
• Familiarity with consumer loan application lifecycle and products is a plus.
• Strong data and analytical skills with proven ability to design, evaluate, and tune ML models.
• Expert in presenting findings, conclusions, and recommendations clearly and concisely.
• Demonstrated initiative-taking, decision-making, and creativity in solving business problems.