Nathan Hutchison
Nathan Hutchison

Nathan Hutchison

Senior Product Manager

I build products at the intersection of data and user experience. B.S. Computer Science, M.S. Engineering Management.

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Experience

Senior Product Manager

Chartmetric

2022 - Present

+ Details

Leading product strategy for a music analytics platform that helps record labels, artists, and managers make data-driven decisions about their careers and catalogs.

  • Own the product roadmap for core analytics features serving major labels and independent artists
  • Lead cross-functional collaboration with engineering, design, and data science teams
  • Conduct user research and translate insights into product requirements
  • Drive feature prioritization based on user feedback and business impact

Product Manager

Sundae

2021 - 2022

+ Details

Built products for a residential real estate marketplace that helps homeowners sell distressed properties.

  • Managed end-to-end product development for marketplace features
  • Worked cross-functionally with engineering, operations, and sales teams
  • Implemented analytics tracking to measure key conversion metrics

Salesforce Analyst

Varian Medical Systems

2019 - 2021

+ Details

Drove Salesforce optimization and data analytics for a leading medical technology company focused on cancer treatment solutions.

  • Led Salesforce system improvements and workflow automation
  • Built dashboards and reports for sales and operations teams
  • Became the go-to technical resource within first year on a new technology stack

Education

Santa Clara University

+ Details

  • M.S. Engineering Management & Leadership
  • B.S. Computer Science, emphasis in Algorithms & Complexity

Selected Work

Music Analytics Platform

Chartmetric

Leading product development for analytics tools that help music industry professionals track artist performance across streaming platforms, social media, and radio.

Problem

Music industry professionals needed a unified way to track artist performance across dozens of fragmented data sources - streaming platforms, social media, radio airplay, and playlist placements.

Approach

Worked closely with users to understand their workflows and pain points. Prioritized features based on user research and data analysis. Collaborated with engineering to build scalable data pipelines and intuitive dashboards.

Outcome

Delivered analytics features used by major record labels and thousands of independent artists to make data-driven decisions about their careers and marketing strategies.

Covid Finance App

Personal Project

A personal finance tracking application built during the pandemic to help visualize spending patterns and budget more effectively.

Problem

During COVID-19, my spending patterns changed dramatically - no commuting, more delivery, different categories. I wanted a way to track and visualize these changes that was more flexible than existing apps.

Approach

Built a Streamlit application in Python that connects to bank transaction data, categorizes spending, and generates interactive visualizations. Used Pandas for data manipulation and Plotly for charts. Focused on making it easy to customize categories and time periods.

Outcome

Built a functional tool that revealed interesting patterns in my spending behavior. The project reinforced the value of building custom tools to solve personal problems and deepened my experience with data visualization.

View on GitHub →

UFC Fight Prediction Model

Personal Project

A machine learning model to predict UFC fight outcomes using historical fighter data and statistics.

Problem

UFC fights are notoriously hard to predict - even experts often get it wrong. I wanted to see if a data-driven approach could outperform baseline predictions and understand what factors most influence fight outcomes.

Approach

Collected historical fight data including fighter stats, reach, age, win/loss records, and fighting styles. Experimented with multiple models including logistic regression, random forests, and neural networks. Feature engineering was key - created composite metrics for fighting style matchups.

Outcome

The model achieved prediction accuracy above baseline, with reach differential and recent win streaks emerging as strong predictive features. The project was a great exercise in feature engineering and working with messy real-world data.

View on GitHub →

Beyond Work

When I'm not building products, I'm usually surfing, skiing, or exploring somewhere new. I also love reading - recent favorite is Behave by Robert Sapolsky.

Tavarua, Fiji Punta Mita, Mexico Sydney, Australia