Mark Koester
Director Of Product at AudioCardio
Los Angeles, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMark Koester is a Director of Product and growth-minded full-stack engineer with 15 years of experience designing and shipping data-centric health, biotech, and AI-enabled products from concept to market. Based in Los Angeles, he blends hands-on engineering (Python, Node, React), UX research, and growth hacking to build DTC and B2B platforms for longevity and diagnostics—most recently growing MyAgingTests.com sales 25% quarter-over-quarter and launching clinical and patient portals for the Clock Foundation. A prolific founder and advisor, he co-created an open-source Quantified Self Ledger that integrates 20+ trackers and demonstrates his strength in time-series data wrangling and personal analytics. He’s led product strategy and growth for startups and clinical teams (Intervene Immune, AudioCardio, MyChon), runs a popular biohacking blog, and has a track record of turning quantitative research into compelling customer experiences. Notably, he bridges international teams and languages, having led China-facing product efforts and cross-cultural startup programs while maintaining a deep interest in biomarkers and longevity interventions.
15 years of coding experience
9 years of employment as a software developer
Language Chinese, Language Chinese at Tourism College of Zhejiang, XiaoshanB.A. Philosophy, B.A. Philosophy at DePaul UniversityLanguage Chinese, Language Chinese at Southwest University for NationalitiesMasters Philosophy, Masters Philosophy at Télécom Physique Strasbourg
Chinese, French, Spanish, English
Github Skills (4)
pandas10
python10
data-analysis10
data-wrangling9
Programming languages (12)
Github contributions (5)
markwk/qs_ledger
May 2018 - Feb 2021
Quantified Self Personal Data Aggregator and Data Analysis
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:76 commits, 4 PRs, 67 pushes in 2 years 9 months
Contributions summary:Mark's commits primarily focus on implementing a fitbit downloader and initial data analysis using Python and the Pandas library. The commits demonstrate the user's ability to read data from a CSV file and perform initial data analysis by creating dataframes and adding features such as weekday. The code indicates a focus on data wrangling and analysis using time-series analysis, suggesting a role in data science.
apple-healthkindle-highlightspythonpersonal-datadata-aggregator
markwk/alfred-workflow-wordcounterapp
May 2018 - Dec 2018
Contributions:2 releases, 19 commits, 14 pushes in 7 months
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