• Build and govern customer data assets: Partner with Data Strategies to define source-of-truth datasets, data definitions, and quality monitoring; document logic and ensure reproducibility. • Data Quality & Integrity: Monitor and improve data accuracy, completeness, and consistency across systems. • GenAI for Commercial enablement: Prototype and evaluate generative AI use cases (e.g., message variant generation, subject line testing, content summarization, agent-assist) with clear guardrails, human validation layer, and measurement. • Stakeholder leadership: Partner on analytics intake and prioritization for CRM and other Commercial platforms; translate ambiguous questions into structured hypotheses, analytical plans, and deliverables. • Commercial measurement and insights: Define and standardize KPI frameworks, translate business needs into clean, usable data models, and communicate data structure insights to leaders and cross-functional partners. • Responsible data & AI: Ensure compliance with data privacy, consent, security, and AI governance policies; identify bias/fairness risks and propose mitigations. • Mentorship: Coach analysts on analytical rigor, SQL best practices, and experimentation while ensuring data quality, governance, and reproducibility.

• Own and grow a regional book of refuse/waste and municipal fleet accounts • Run the full cycle: prospect, demo, pilot, close, and expand on a per-truck subscription model • Win competitive municipal RFPs and navigate public-sector procurement • Partner with our dealer channel and body/OEM partners to source and close deals • Structure multi-year subscription agreements and pilots with clear, written success criteria • Be the voice of the customer back to product as we build the roadmap

Role Description The University of Arkansas for Medical Sciences (UAMS) has a unique combination of education, research, and clinical programs that encourages and supports teamwork and diversity. We champion being a collaborative health care organization, focused on improving patient care and the lives of Arkansans. The safety of our team members at UAMS is our top priority. For this reason, successful applicants for this position must be fully vaccinated against Covid-19 or have an approved medical or religious exemption on file with our Student & Employee Health Services dept. UAMS will adhere to all federal, state and local regulations and will obtain necessary proof of vaccination prior to employment to ensure compliance. Below you will find the details for the position including any supplementary documentation and questions you should review before applying for the opening. To apply for the position, please click the Apply link/button. Qualifications - n/a Requirements - Persons must have proof of legal authority to work in the United States on the first day of employment. Benefits - All application information is subject to public disclosure under the Arkansas Freedom of Information Act. Company Description The University of Arkansas is an equal opportunity, affirmative action institution. The University does not discriminate in its education programs or activities (including in admission and employment) on the basis of age, race, color, national origin, disability, religion, marital or parental status, protected veteran status, military service, genetic information, or sex (including pregnancy, sexual orientation, and gender identity). Federal law prohibits the University from discriminating on these bases. Questions or concerns about the application of Title IX, which prohibits discrimination on the basis of sex, may be sent to the University's Title IX Coordinator at this link and to the U.S. Department of Education Office for Civil Rights. For general application assistance or if you have questions about a job posting, please contact Human Resources at askrecruitment@uams.edu .

• Set and lead the strategy for data engineering, AI engineering, and foundational data services, ensuring scalability, efficiency, and alignment to business outcomes. • Ensure an end‑to‑end lifecycle from diverse raw data sources—including IoT, field data, and factory/production systems—through engineering, modeling, deployment, monitoring, and operational insight. • Lead global teams across data architecture, data engineering, integration engineering, and data operations. • Establish and enforce standards for coding, observability, resiliency, SLIs and SLOs, incident response, and operational playbooks. • Own global AI capability capabilities including compute environments, MLOps tooling, AI operational workflows, and model hosting capabilities. • Deliver reusable AI capability components that streamline model development, deployment, monitoring, and audit readiness. • Drive global convergence of data and AI capabilities, toolsets, engineering patterns, and operational processes. • Enable secure, governed self service for data, analytics, and AI so teams can build on standardized capabilities with confidence. • Own reliability, availability, observability, and security across all data and AI capabilities. • Oversee global monitoring, incident management, problem management, capacity planning, disaster recovery, and lifecycle management. • Build organizational capability through workforce planning, skill development, mentoring, and global alignment.