Jonathon Sill

Authored new proforma model to identify impact of proposed contract rates on gross margin and inform Managed Care leadership of avenues for consideration in further negotiation with patient payors

Conducted analysis of lowest-performing contracts for FY2021 to inform upcoming contract renegotiations, created new revenue projections based on historical payor performance across multiple negotiation scenarios

Developed reporting suite to monitor customer acquisition cost (CAC) & lifetime value (LTV) by channel and cohort

Authored attribution model to optimize marketing spend in existing markets and inform strategy into the launch of two new markets

Performed market analysis across potential launch destinations and created quant document to shortlist top markets based on consumer expenditure and census data

Managed paid media campaigns across online channels with average monthly spend surpassing $100k

Managed team of two employees dedicated to facilitating technical needs of Medical Economics Division

Collaborated with Business Intelligence leadership to establish data pipelines and requirements from Medical Economics data warehouse into DOMO, PowerBI & IBM TM1

Led renegotiation of large-national payor contract and conducted profitability analysis of proposed fee-for-service and capitated agreement scenarios resulting in an estimated $700k annual increase to net revenue

Authored executive level model investigating payor claims data to determine the impact of Covid-19 on patient Durable Medical Equipment utilization trends by geographical region over time

Created pricing model for Medicare Competitive Bid Round 2021 using historical data to forecast future Durable Medical Equipment Medicare rates

Utilized third-party Centers for Medicare and Medicaid Services data to identify Apria Healthcare market share across Competitive Bid Area regions and develop Medicare Round 2021 bid strategy

Analyzed contract profitability and provided recommendations to Strategic Relations team with the viability of proposed payor fee schedules and considerations for further negotiation

Performed ad-hoc SQL analyses, IBM TM-1 data validation, and monthly reporting

Monitored statistical trends in large-cap cryptocurrencies to establish daily positions and execute trades

Utilized Python to develop Bitcoin price-predicting trading bot using advanced mathematical interpolation methods to predict future candle statistics in real-time

Hosted community Discord server dedicated to option-trading education, Q&A, and monitoring of personal trades with entry/exit points and dialog

Collaborated with Space Launch System (SLS) contractors to create Stennis Space Center (SSC) fault tree analysis and calculate failure probability for NASA hardware components 

Performed User Acceptance Testing (UAT) on proprietary incident reporting software

Co-lead of an Independent Investigation (II) team designated to provide a technical analysis of a critical engine system failure and present recommendation to resume engine testing to executive leadership team

Calculated Maximum Credible Event (MCE) for SSC engine test stands/ordnance locations and assisted with implementation of findings into SSC Geographic Information Systems (GIS) software.

Member of J-2X & RS-25 Engine hot-fire test teams

Completed B.S. in Computer & Information Science with a focus in Digital Content and Information Systems

Cumulative GPA: 3.82 | Major GPA: 4.0

Pursued B.S. in Aerospace Engineering

Early college entrance program for gifted students in Beaumont, TX. Graduated with 60 hours college credit.

Exam Prep: CFA® Level 1 Bootcamp 2020 Curriculum Part I

Financial Accounting I (NASBA Official Certification)

Complete PostgreSQL Course for Data Science
Learning ETL Using SQL Server Integration Services
dbt Fundamentals (Official dbt Training Course)

Introduction to Graph Databases (Official Neo4j Training Course)
Data Modeling in Graph Databases (Official Neo4j Training Course)

Python 3 Complete Masterclass: 2018 Edition

Tableau 10 A-Z: Hands-On Tableau Training for Data Science