Open for work Data science for finance, tech, and healthcare

Hi! 🇺🇸

Chase's Portfolio

I'm a prospective Data Scientist with real-world experience applying analytics and machine learning to healthcare research, biopharma strategy, and financial operations. I want to use data and technology to help others, solve meaningful problems, and spark curiosity. That curiosity shows up outside my career too, from learning the album Shawn on guitar to studying three languages.

See my work Get in touch
6
Data projects
$1.2M+
Spend analysis led
$100K+
Budget recommendations
Portrait of Chase Patterson

A bit about me.

Curious by default, from clinical trial data to a new chord progression.

I want to experience as much of life as I can, from different perspectives and professional careers to the smaller details that make me, me. That could be a clinical trial dataset, music, languages, or neuroplasticity.

For most of my life, that curiosity and energy went into sports. I was always playing something, always moving, and always looking for the next challenge. Then I tore my ACL during my freshman year of college, and that part of my life changed forever. For a while, I became complacent, feeling stuck and stopped pushing myself to grow. College brought more difficult challenges that often felt like climbing a muddy hill. There were times when progress felt slow, but each challenge forced me to adapt and find a different way forward. Over time, I started putting that same energy into areas I had never explored as deeply before — the arts and sciences. Challenging myself in those areas has become a big part of how I approach learning, work, and life today.

At Avalyn Pharma, I spent almost a year in Corporate Development and three months in Finance. I moved the team's CRM off spreadsheets and into Salesforce, built KPI dashboards, and put together financial models that went straight to the CFO. The biggest lesson was a humbling one: nobody cares how clever an analysis is if they can't understand it in the two minutes they have.

After my two internships wrapped up, I wanted to keep learning about this space on my own, with questions like "Does the market actually understand what's happening in IPF clinical trials?" I answered it using only public data: first a database of every IPF/PF trial I could find, then a stock-market event study built on top of it. Healthcare data also hits close to home for me. Not just personal battles, but my uncle was diagnosed with Parkinson's disease, and since then I can't see health data as just rows in a table.

I've also taught martial arts for over a decade, which taught me that if a student doesn't get it, the problem is usually how I explained it. Outside of that, I'm an intermediate guitar player working through Shawn Mendes' album Shawn and recording my practice sessions along the way. I'm also studying Italian (thanks to my mom's side of the family), French, and Spanish.

The toolkit.

The languages, tools, and methods behind my projects and internship work.

Filled skills are the ones I use most.

Languages & databases

  • Python
  • SQL
  • PostgreSQL
  • Snowflake
  • CTEs & window functions

Data engineering

  • PySpark
  • dbt
  • Docker
  • Git & GitHub
  • REST APIs
  • ETL pipelines
  • Data cleaning
  • Data quality checks

Analysis & ML

  • pandas
  • NumPy
  • scikit-learn
  • SciPy
  • Classification
  • Logistic regression
  • Random forest
  • Model evaluation
  • Feature engineering
  • K-means & hierarchical clustering
  • PCA
  • Hypothesis testing
  • Event studies
  • Wearable sensor data
  • Missing-data analysis

Visualization & reporting

  • Tableau
  • Matplotlib
  • Seaborn
  • KPI dashboards
  • Jupyter

Business & finance

  • Excel
  • Salesforce
  • NetSuite
  • Workday Adaptive Planning
  • Financial modeling
  • Spend analysis
  • Deal benchmarking

Work I'm proud of.

Real problems. Real data. Real results.

Connected study

Does Wall Street accurately price IPF science? Two projects built on one shared PostgreSQL database. The trial database feeds the stock-market event study.

SQL, data engineering, ML Completed

IPF/PF Clinical Trial Intelligence Database

An end-to-end pipeline pulling ~575 IPF/PF clinical trials from the ClinicalTrials.gov API, enriched with openFDA approval outcomes and loaded into a normalized five-table PostgreSQL database running in Docker.

Antifibrotic trials led on both scale and outcome: 35.3% reached Phase 3+ and 86.4% completed, tracking with the only mechanism class backed by FDA-approved IPF drugs.

Tagged ~912 interventions by mechanism class, wrote four SQL analyses with CTEs and window functions (sponsor ranking, phase funnel, mechanism success rates, duration benchmarks), and built a logistic regression model that scored 100 active trials for termination risk. Published as a four-view Tableau Public story.

  • PostgreSQL
  • Docker
  • SQL window functions
  • Python
  • scikit-learn
  • REST APIs
  • Tableau
View on GitHub Open Tableau dashboard
Finance, event study, biopharma Completed

IPF/PF Biopharma Trial Event Study

Measures how the stock market reacts to IPF/PF trial milestones. Using the publicly traded sponsors flagged in the trial database, I pulled 113K+ daily price rows across 31 tickers and computed cumulative abnormal returns around 270 trial events.

Phase 3 trial starts drew the strongest selloff (mean CAR −3.3%), and small-cap biotechs reacted 5–10x more than large pharma.

Built a standard event study in Python (5-day event window, 60-day estimation baseline, two-tailed t-tests) and wrote results back to the shared Postgres database. The honest finding: only ~5–11% of events were statistically significant, so the market doesn't systematically misprice IPF trials. The signal lives at the tails.

  • Event study
  • Python
  • yfinance
  • SciPy
  • PostgreSQL
  • Financial analytics
  • Tableau
View on GitHub Open Tableau dashboard
AI usage, data engineering In progress

Offloaded

Measuring the shift from AI-as-tool to AI-as-thinker, 2022–2026

An honest look at how students and everyday people have come to rely on AI since 2023, my senior year of high school, and whether we're still doing our own thinking.

Core question: when did AI stop being a tool we use and start being something we hand our thinking to?

Early build phase. The pipeline is scaffolded for ingestion, dbt models, and Spark processing, and I'm writing the core code myself. Methodology and findings are coming as the analysis takes shape.

  • Python
  • SQL
  • PySpark
  • dbt
  • Data pipelines
  • AI usage
View on GitHub

More projects.

Healthcare machine learning, wearable data, and unsupervised learning.

Healthcare ML Completed

Parkinson's Detection from Voice

Classifies healthy vs. Parkinson's voice recordings using acoustic features like jitter, shimmer, and pitch irregularity that the ear can't pick up.

Built a scikit-learn pipeline with feature selection and scaling, evaluated on accuracy, precision, and recall. A handful of vocal features carried most of the predictive signal.

  • Python
  • scikit-learn
  • Random forest
  • Feature selection
View on GitHub Read the report
Wearables, industry collaboration Completed

Social Interaction Patterns in Parkinson's

With SocialBit, I analyzed a month of wearable data (heart rate, movement, activity states) to test whether a Parkinson's patient's social interactions break into shorter, fragmented blocks.

Found 4–6 hour gaps on some days and chose not to treat them as zero activity, so time-of-day claims stayed off the table. Data quality came before conclusions.

  • Wearable sensor data
  • Python
  • Missing-data analysis
View on GitHub
Unsupervised learning Completed

Exoplanet Clustering

Grouped 4,855 known exoplanets by mass, radius, orbit, and temperature to see whether planet types emerge on their own, without labels.

K-means (elbow method) and hierarchical clustering separated small, cooler planets from hot, massive Hot Jupiter-type planets, visualized in 2D with PCA.

  • K-means
  • Hierarchical clustering
  • PCA
  • scikit-learn
View on GitHub

Off the clock.

Two things I'm learning just because I love them.

Learning Shawn on guitar

Since Oct 2026

Working through Shawn Mendes' 2024 album Shawn song by song with up to 60 minutes a day of spaced practice. I record my sessions so I can hear each song come together.

  • Guitar
  • Spaced practice
  • Session recordings

Italian, French & Spanish

Ongoing

Learning the three major Romance languages, inspired by my mom's Italian heritage, through immersion, grammar study, and conversation, with an eye on the Latin roots they share.

  • Italian
  • French
  • Spanish (Colombian)
View on GitHub Notion tracker

Where I've been.

Applying data skills in real organizations.

May 2025 – Mar 2026, Boston, MA

Finance & Corporate Development Intern

Avalyn Pharma

Operated across two high-visibility functions with direct exposure to C-suite decision-making for a clinical-stage biopharma company.

  • Spearheaded migration of the Corporate Development CRM from a manual Excel system to Salesforce in 10 weeks, streamlining stakeholder engagement and presenting the full build to the CFO/CBO and G&A leadership.
  • Built a comparative biopharma transaction benchmarking database analyzing upfronts, milestones, and royalty structures across modalities, used directly in BD valuation discussions.
  • Developed a clinical trial landscape dashboard integrating competitive trial data to identify design trends and whitespace opportunities for corporate strategy.
  • Constructed KPI dashboards across Investor Relations, Business Development, and Banking, giving the CEO and CFO real-time insight into capital raising and partnership status.
  • Conducted T&E spend analysis of $1.2M+; identified $100K+ in reallocation opportunities by analyzing spending outliers and trends.
  • Mapped Procure-to-Pay and AP workflows with Finance, Legal, and HR; developed three process flowcharts presented to the CFO/CBO and VP of Finance.
  • Managed vendor data trackers for ~150 vendors and 220+ POs to improve forecasting accuracy through FY25.
Chase Patterson presenting during an Avalyn Pharma presentation in front of a projected slide.
Apr 2023 – Jun 2025, Chapel Hill, NC

Lead Martial Arts Instructor

Impact Fitness & Martial Arts

11 years of martial arts experience applied to designing tailored programs for students of all ages at a newly established studio. Improved enrollment and student retention through consistent leadership, communication, and adaptability across diverse learning needs.

A younger Chase Patterson holding multiple martial arts medals.

Let's connect.

Reach out about roles, projects, or just to chat.

What makes me different

The human side of data science

11 years of teaching martial arts has made me a better communicator than any course could. I know how to explain complex ideas to someone who's never heard them before, whether that's a six-year-old learning a kick or a CFO reviewing a complex dashboard. I show up curious, clear, and ready to listen.

I'm actively looking for full-time roles starting Summer/Fall 2026 in Data Science, Applied Analytics, and ML Engineering.

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