About
Three years of client-facing data science at Viasat, Merck, and Elevance Health. Shipping ML systems from research to production.
Experience
Project Manager & Technical Lead
The Data Mine – Elevance Health · West Lafayette, IN
Led a team of ~15 student data scientists in an Agile environment, owning technical strategy and model direction for healthcare cost prediction and patient segmentation initiatives.
- Directed sprint planning, stakeholder communication, and technical mentorship across multiple workstreams
- Built cost-of-care prediction models translating outputs into actionable financial and operational insights
- Developed patient clustering and segmentation analyses for targeted healthcare interventions
- Owned model direction and strategic guidance, presenting findings to senior healthcare leadership
Data Science Intern – Pharmaceutical R&D
Merck & Co. · West Point, PA
Redesigned HPV vaccine assay optimization workflow, replacing legacy linear regression with statistically rigorous hypothesis testing to dramatically improve throughput and processing time.
- Identified that the 64-well spectroscopic assay decision problem was threshold-based classification, not regression
- Designed and implemented two-sided t-test framework replacing computationally expensive regression workflow
- Reduced assay processing time from ~1 day to ~3 hours while increasing throughput 10x
- Presented findings to senior scientific staff, successfully advocating for adoption of new methodology
- Demonstrated willingness to challenge legacy processes with data-backed reasoning
ML Systems Integration Engineer
The Data Mine – Merck · West Lafayette, IN
Transformed complex Python-based ML research artifacts built by PhD researchers into automated, scalable Dash web applications accessible to non-technical stakeholders.
- Parsed complex ML research codebases using advanced regex and pipeline automation techniques
- Built automated ML-to-Dash integration pipelines converting fragmented research into interactive tools
- Developed user interfaces that made sophisticated models accessible to business stakeholders
- Collaborated with PhD researchers to understand model architectures and preserve scientific rigor
Computer Vision Research Associate
The Data Mine – Viasat · West Lafayette, IN
Applied self-supervised learning techniques to satellite image segmentation during first year of undergraduate study, working alongside advanced researchers in a graduate-level computer vision engagement.
- Implemented self-supervised learning methods for representation learning on satellite imagery
- Collaborated with senior researchers on experimental design and iterative model development
- Rapidly upskilled in computer vision fundamentals and deep learning frameworks
- Participated in Agile workflows with weekly sprints and technical reviews
Healthcare Marketing Analytics
Enterprise Healthcare Client · Remote
Analyzed Medicare and Medicaid datasets to identify underrepresented but reachable patient populations for GLP-1 therapies (Wegovy, Ozempic), translating analytics into targeted outreach recommendations.
- Processed large-scale Medicare and Medicaid datasets to identify patient population segments
- Developed segmentation logic balancing reach, equity, and therapeutic appropriateness
- Translated analytical findings into actionable marketing and outreach recommendations
- Considered equity implications in targeting strategies for underrepresented populations
Skills
Core Programming
ML & Statistical Modeling
Data Systems & Visualization
Cloud & Deployment
Education
Bachelor of Science in Computer Science in Machine Learning Concentration
Purdue University
West Lafayette, IN · 2021 - 2025
- Three years of Data Mine corporate partnership experience (Viasat, Merck, Elevance Health)
- Published research in healthcare machine learning
- Coursework: ML, Computer Vision, Statistical Learning, Distributed Systems