The Test Set by Posit Emily Riederer: Column selectors, data quality, and learning in public
Jan 26, 2026
Emily Riederer, a data science manager at Capital One and cross-language tool author, talks about her journey through R, Python, and SQL. She dives into messy real-world data, the rise of dbt and better SQL tooling, and why column selectors (yes, really) change ergonomics. She also discusses learning in public, imposter syndrome, and solving boring but high-impact problems.
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First Data Mistake That Changed Her View
- Emily Riederer first met messy real-world data during an internship when averaging incomes mistakenly included a 99999 default value.
- That mistake revealed to her that data is chaotic and not the objective ground truth she expected.
Data Modeling Is An Art That Prevents Chaos
- Emily found an 'art' to organizing databases and extracting data that sets analytics up for success.
- Thoughtful data modeling and extraction can dramatically reduce downstream chaos and errors.
Three Hats At Capital One
- At Capital One, Emily rotated through measurement, tooling, and back to modeling, wearing three distinct hats over time.
- That movement led her to focus on upstream engineering to improve analysts' lives.