Data Scientist & Analytics Architect; Oklahoma , Ok
Listed on 2026-03-01
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IT/Tech
Data Engineer, Data Analyst, Data Science Manager
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
- 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
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