Dr. Powers holds a doctorate in Experimental Psychology and Behavioral Neuroscience from Purdue University and completed a National Institutes of Health (NIH) Postdoctoral Fellowship in Quantitative and Statistical Genetics at the Institute for Behavioral Genetics (CU Boulder).

His academic research focused on behavior change, combining behavioral, biochemical, statistical, and pharmacological approaches to isolate complex genetic, neurobiological, and environmental drivers of health. This experience laid the blueprint for a career defined by peer-reviewed scientific rigor.

Driven to see data directly improve real-world outcomes, Matt transitioned from academia to lead cross-functional analytics and outcomes teams across digital health platforms, AI-powered health plan analytics, and healthcare consulting organizations focused on behavior change.

• Outcomes Leadership & COE Co-Founder: Co-established an enterprise Advanced Analytics Center of Excellence. Led cross-functional divisions—bridging clinical, product, sales, and software engineering teams—to set data governance standards and standardize product-specific value KPIs.
• Advanced Analytics Translation: Managed teams of healthcare analytic consultants deploying supervised and unsupervised machine learning, predictive modeling, and quasi-experimental design to optimize healthcare cost, quality, and service initiatives.
• Executive Strategy & Advisory: Trusted advisor who regularly presents complex analytic narratives to C-suite executives, pharmaceutical marketing teams, health system leads, and Medicare Advantage summit leadership.

Matt founded Based Analytics to do data science "the right way." By applying rigorous scientific methodologies to complex business and population health challenges, Based Analytics eliminates data noise and delivers actionable, precision-targeted risk intelligence.

• State-Wide Health System Analytics: Collaborated with health system leadership to develop predictive SDoH resource allocation models directly supporting Community Health Needs Assessments (CHNA) and Community Health Improvement Plans (CHIP) for CMS submission.
• Predictive Risk Adjustment & Outcomes: Designed and implemented innovative quasi-experimental and predictive modeling approaches that significantly boosted key claims-based outcomes and risk-adjustment accuracy.
• Regional Measurement Expansion: Expanded corporate consulting engagements across regional health directors to establish localized measurement and interpretation strategies tailored to specific community demographics.