Data · Applications · AI-Accelerated Delivery
Technology people actually adopt.
I build and modernize data products, workflow applications, forecasting tools, and operational software—and create the delivery paths that turn them into everyday practice.
Jonathan “Jono” Schulein · Charlotte, NC · Open to relocation
About
From ambiguity to adopted technology.
I work across data, applications, AI-assisted software development, and delivery, translating ambiguous operational problems into tools that people can use, trust, and sustain.
My experience includes modernizing a machine-learning application, automating data pipelines, building executive analytics, developing clinician-facing workflow tools, and leading readiness for a national service transition.
I currently work at a large government consulting firm, where for eight-plus years I have supported complex healthcare and public-health environments. I often operate at the intersection of technical execution, stakeholder needs, and implementation—determining not only what should be built, but what it will take for the solution to succeed in practice.
Capabilities
Technical range, anchored in delivery.
I am most useful where a problem crosses boundaries: data and operations, software and users, technical implementation and organizational change.
Data & modeling
- Python, pandas & SQL
- Power BI & Tableau
- Forecasting & Monte Carlo simulation
- Data quality, automation & analysis
Applications & AI
- ML application modernization
- Python, Flask & JavaScript workflows
- AI-assisted software development
- Power Apps, SharePoint & Microsoft Lists
Release & delivery
- Containerized & local deployment
- UAT, regression & workflow testing
- Release readiness & packaging
- Documentation for non-technical users
Product & operations
- Stakeholder discovery & executive engagement
- Business process analysis & improvement
- Change management & implementation
- Alternatives analysis & decision support
Selected work
Projects that moved from analysis to adoption.
Four examples of taking complex work through discovery, technical execution, validation, and real-world use.
TowerScout: from research prototype to release-ready
Modernized a computer-vision research application into a package-based local application path designed for non-technical pilot users.
- Challenge
- TowerScout identifies cooling towers in aerial imagery to support state and local Legionnaires' disease outbreak investigators. It began as a successful research project — and as interest in the tool grew, the setup time and technical comfort it required became the main barrier for new users.
- Contribution
- I led the modernization workstream, using AI-assisted development under structured human review to map the inherited codebase, plan and implement fixes, and validate behavior. Building on the original team's foundation, I resolved 90% of the major workflow issues surfaced in user-journey testing, replaced routine configuration-file editing with guided first-launch setup, and refined how search areas were tracked so processing behavior consistently matched what users drew on the map.
- Result
- Delivered and validated a Windows pilot path with containerized runtime support, readiness checks, checksum-verified assets, plain-language documentation, and UAT criteria for non-technical testers. The application is now in user testing.
988: forecasting a national crisis line's biggest change
Built the forecasting foundation and helped lead the operational readiness work behind a high-visibility national service transition.
- Challenge
- A national crisis line needed to understand how a new three-digit number could change contact volume because staffing, technology support, and operational readiness all depended on the answer.
- Contribution
- Working within the program management team, I designed and built the Monte Carlo simulation behind the volume projections, incorporating growth trends, market saturation, and international precedent. I presented the methodology to senior executive leadership, earned approval for the planning assumptions, led cross-functional readiness workstreams, and developed the alternatives analysis for text and chat operations.
- Result
- The projections anchored staffing and readiness planning, 988 went live on schedule in July 2022, and the client's assessment was that the organization had been over-prepared rather than underprepared.
Clinical and operational tools built into the workday
Created analytics and workflow tools that helped clinicians, hospital leaders, and innovation teams make decisions inside the systems they already used.
- Challenge
- Three healthcare program offices needed better access to clinical guidance, clearer operational reporting, and more structured processes for research review and innovation governance.
- Contribution
- Working with delivery teams across the three offices, I transformed long-form clinical guidance into an interactive SharePoint knowledge base and built Power Apps and Microsoft Lists tools that formalized SME decision-support and voting workflows. I led development of our team's Power BI reporting for quality performance and document-review backlogs, and maintained the innovation project portfolio dashboard — developing ad-hoc views to support governance decisions across a multi-million-dollar portfolio.
- Result
- Tools entered production use across all three offices, the clinician team provided direct written praise, and the research process I built supported development of two additional peer-reviewed guidance papers.
Data-driven modernization at national scale
Turned fragmented operational data and local practices into decision-ready analysis, automation, dashboards, and a repeatable regional transition model.
- Challenge
- A national healthcare system needed a clearer view of contact-center maturity and performance while individual regions and medical centers operated with different processes, data practices, and levels of readiness.
- Contribution
- Serving as the data lead across several team engagements, I led analysis of a 450+ respondent field survey, converted qualitative responses into weighted scoring across nine core elements, automated recurring performance reporting with Python, and built Tableau reporting used during COVID-19 operations. I later project-managed one region's consolidation across eight historically siloed medical centers as they adopted a new enterprise platform.
- Result
- Automation reduced a 6–8 hour process to minutes, all eight sites transitioned successfully, and the consolidation artifacts became a template reused by other regions and a case study for the wider initiative.
Approach
How I move ambiguous work into production.
The projects change—a crisis line, a hospital network, a public-health application—but the operating principles stay consistent.
01
Discovery before delivery
Every legacy system has a folklore layer: decisions that once made sense for reasons nobody documented. I start by comparing what actually happens with what the documentation claims—whether that means synthesizing 80+ staff interviews or tracing execution paths through an inherited codebase. The goal is a prioritized backlog small enough to execute well.
02
Right-size the tool
The best solution is one the organization can use and sustain. The 988 model lived in Excel because executives needed to interrogate it. Repetitive reporting moved to Python because manual processing consumed a workday. Clinician workflows used the Microsoft tools clinicians already worked in every day — familiarity I could build on to tailor solutions the client could confidently manage after handoff. TowerScout required containers, packaging, and readiness checks because a research workflow would not survive contact with non-technical users.
03
Adoption is the finish line
A tool that ships but is not used is still unfinished. I treat the last mile as part of the product: plain-language guides, workflow-based testing, support-friendly diagnostics, and handoff materials written for the person who will own the solution. Walking the full user journey often reveals the failures that isolated technical tests miss.
04
AI-accelerated, human-accountable
I use AI coding tools daily for codebase discovery, task planning, drafting, test scaffolding, and first-pass diagnosis. They accelerate the work; they do not inherit the responsibility. User-visible behavior, configuration, and releases still pass through human review and structured testing. My rule is simple: I ship nothing I cannot explain, defend, and debug without the AI in the room.
Recognition
Trusted with the hard, ambiguous work.
Recognized through multiple performance and team awards spanning simulation modeling, analytics, clinical workflow tools, and application modernization.
“Gratitude to Jono for continuously going above and beyond in his thoughtful, generalizable and impactful Decision Support Tool creation, so that future teams will be empowered.”
— Client clinician team
“When we met with the client they were crystal clear that maintaining [the firm] meant maintaining Jono. That is a very strong testament to the quality of work he has been delivering.”
— Program Manager, consulting firm
“His ability to take high-level visions and transform them into thoughtful, high-quality deliverables made him one of the most valuable members of a very talented team.”
— Project colleague, consulting firm