DATA SCIENTIST & ANALYTICS ARCHITECT

ADVANCE YOUR CAREER WHILE SAVING LIVES

Location: Oklahoma City, OK

Salary: Competitive salary based on education and/or experience and holiday pay and $500 bonus after 6 months and $1,000 bonus after 1 year!

Benefits: Health, dental, vision, life insurance, long-term disability, 401(k), paid time off, $5,000 annual tuition reimbursement, etc.

Days: Monday through Friday

Hours: 8:00 a.m. to 5:00 p.m.

Position:

The Data Scientist & Analytics Architect serves as the enterprise leader for data architecture, analytics strategy, data engineering, and responsible AI adoption. This hands-on leadership role ensures organizational data is trusted, scalable, governed, and aligned with measurable business outcomes. You will shape how data drives enterprise decision-making and individualize donor impact through meaningful, data-driven engagement.

Qualifications:

• Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or related field
• 10+ years in enterprise data architecture, analytics, or data engineering; 5+ years in senior technical leadership
• Deep expertise in SQL, dimensional modeling, ETL/ELT, and with experience building an enterprise data warehouse
• Experience modernizing or building scalable enterprise data platforms
• Strong executive communication skills with the ability to align analytics to business KPIs

Primary Responsibilities:

• Design and enforce enterprise data architecture, modeling, and integration standards
• Lead development and modernization of the Electronic Data Warehouse (EDW)
• Establish data governance, quality standards, and scalable analytics infrastructure
• Deliver KPI-aligned analytics that drive measurable business value
• Partner with operational and executive leaders to translate data into strategic insights
• Lead and mentor Data Engineers while overseeing SQL, ETL/ELT, and pipeline design
• Ensure performance, reliability, automation, and integrity of enterprise data systems
• Identify and implement practical AI use cases aligned with business priorities
• Establish governance and best practices for responsible AI adoption
• Develop data-driven engagement strategies that recognize and inspire blood donors