Featured Projects
A selection of data visualization projects built with Tableau, designed to tell meaningful stories through data.
Dynasty Fantasy Football Dashboard
Problem: Dynasty fantasy managers needed a way to analyze weekly consistency and long-term player value across seasons.
This Tableau dashboard visualizes 5 years of player data from the Sleeper API (2019–2024), focusing on performance by position (QB, RB, WR, TE). Users can dynamically filter by season, position, and top rankings to uncover key trends.
- Compare average weekly and seasonal performance by position
- Track consistency with 4-week moving averages
- See which positions retain value deeper into the season
- Interactive filters for season, position, and custom Top X
Business Dynamics Statistics Explorer
As a Lead Data Analyst at the U.S. Department of Commerce, I helped build and optimize the BDS Explorer — a national dashboard that tracks job creation and firm startups across the U.S. economy.
I led efforts to automate data pipelines using SQL and Python, improved time series reliability across a 45-year span, and designed interactive visualizations to help economists, journalists, and policymakers explore trends by firm age, industry, and geography.
Visit BDS ExplorerAbout Me
Hey, I’m Spencer — a data analyst with 12+ years of experience turning complex datasets into powerful, easy-to-understand stories. I specialize in building scalable dashboards, streamlining data workflows, and uncovering insights that help people make smarter decisions.
I’ve worked with millions of rows of data, led a federal analytics team, and created public-facing dashboards used by journalists, economists, and business leaders. My toolkit includes SQL, Python, Tableau, and just enough R to be dangerous.
Whether it’s cleaning messy datasets, visualizing a 45-year time series, or automating a pipeline that saves hours of manual work — I’m all about creating clean, reliable, and actionable solutions.
Tools & Skills
Here’s what I bring to the table — technical expertise, analytical thinking, and a passion for solving real problems with data.
Languages & Libraries
- SQL
- Python (Pandas, NumPy)
- R
- SAS
Data Visualization
- Tableau
- Power BI
- Matplotlib / Seaborn
- Google Analytics
Tools & Platforms
- Snowflake
- Advanced Excel
- Google Sheets
- AWS (Cloud Practitioner)
Soft Skills
- Team Leadership
- Process Improvement
- Clear Communication
- Project Management
How I Work With Data
1. Discover the Why
Everything starts with a question. Whether it’s “Why are startups declining?” or “Where is job growth strongest?” — I begin by understanding the business challenge.
2. Design the Pipeline
Using SQL, Python, or SAS, I build repeatable pipelines to structure and clean large datasets — setting the stage for solid analysis.
3. Analyze What Matters
With a cleaned dataset, I dig deep — uncovering trends, outliers, and stories. I use Tableau and statistical tools to turn numbers into insight.
4. Deliver With Clarity
The end result is a visual story: dashboards, presentations, or datasets that are intuitive, clean, and built for action.
What People Say
Kind words from teammates, collaborators, and project leads:
“Spencer provides excellent customer service and is exceptionally reliable. He demonstrates unusually good leadership skills and showcases his ability to manage a large-scale program. Spencer is an excellent team player and routinely collaborates with coworkers, creating a highly successful cooperative effort and contributing significantly to the accomplishment of organizational goals.”
— Melissa Kopajtic, Manager
“Spencer is a fantastic colleague. His high technical acumen is paired with an ability to explain difficult concepts in understandable terms. He leads by example and routinely motivates others. Having worked with Spencer for the past three years, I've seen first hand how our team's productivity has benefited from his leadership.”
— Richard Beem, Colleague
Let’s Connect
Whether you’re looking for a data analyst to join your team, collaborate on a project, or just chat about data — I’d love to hear from you.