Data engineering
Reconcile records across systems, build ingestion and transformation pipelines, and prepare and validate data migrations.
Data architecture · Engineering · Analytics
Reliable data. Repeatable workflows. Decisions grounded in evidence.
I help organizations reconcile data, automate recurring work, prepare migrations, and develop or evaluate forecasts. I founded LeanLogic Systems and lead the architecture and development of Exauren, our domain-intelligence platform.
Client services
Defined problems. Practical deliverables.
I translate business objectives into scoped data engineering, automation, and analytical engagements, including defined work packages for consulting and technology partners.
Workflow automation
Automate recurring processing, validation checks, and reporting, with clear requirements and traceable results.
Predictive analytics
Develop forecasts, evaluate models against meaningful baselines, and make uncertainty and limitations explicit.
Each engagement starts with the available inputs, constraints, scope, and acceptance criteria. I provide architectural direction, guide implementation, and verify deliverables. Documentation and handoff are included in the agreed scope.
Explore LeanLogic Systems client services →Applied research
Exauren
Exauren is LeanLogic Systems’ domain-intelligence platform in development for complex, high-obligation environments. Its architecture distinguishes statistical inference, rule-verified facts, and unresolved evidence.
Explore Exauren research →Current application: U.S. occupational safety. Research characterizes the establishment population using mandated OSHA injury data and evaluates whether preventive attention can be concentrated where consequential enforcement outcomes are subsequently observed.
The platform is designed for adaptation across domains. Its research emphasizes traceable evidence, explicit uncertainty, and defensible claim boundaries.
Selected portfolio
Academic work samples
These projects were completed as coursework in the MIT Professional Education Applied Data Science program. They provide examples of model development and evaluation through public notebooks and recorded outputs. They are academic work, separate from paid client delivery and Exauren research.
Computer vision · Image classification
Malaria Detection
Classification of parasitized and uninfected red-blood-cell images. An academic exploration of image preprocessing, neural-network models, and evaluation; not a clinical diagnostic system.
Deep learning · Digit recognition
SVHN Recognition
Digit classification using Street View House Numbers image data. The notebook explores dense and convolutional neural networks and records differing model outcomes.
Background
Experience across operational domains
My experience includes more than a decade of analytics and data infrastructure work within a Fortune 500 supply-chain organization, along with healthcare data engineering and higher-education analytics.
Across these settings, I connect requirements, data, implementation, and evidence so that results can be inspected, understood, and used responsibly.
View professional experience on LinkedIn →- M.S., Predictive AnalyticsNorthwestern University
- B.S., MathematicsNortheastern State University
- Applied Data Science Program CertificateMIT Professional Education
Scoped projects & delivery partnerships
Let’s define a useful first deliverable.
Describe the result you need, the data or systems involved, and your timing. Based in Knoxville, Tennessee; available for remote engagements.
- Project inquiries
- michael@exauren.ai
- Company contact
- michael@leanlogic.ai