Maxfield Frohlich
Principal Data Scientist
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMaxfield Frohlich is a Principal Data Scientist based in San Jose with eight years of experience building ML forecasting and GenAI systems that drive finance decisions in pharma. At Genentech he owns the ML forecasting layer for a global revenue engine informing $60B in annual predictions and has translated model insights into capital allocation tied to billions in revenue and millions saved in reserves. His background in healthcare outcomes research and hands-on work at startups gave him deep expertise in causal inference and production ML, from patient-selection algorithms to structured metadata extraction pipelines. He contributes to the popular sktime time-series library, adding robust live-forecasting utilities like FallbackForecaster and realistic cross-validation splitters that reflect deployment conditions. Comfortable working end-to-end, he blends technical rigor with business impact—optimizing models where small improvements materially change financial decisions. He frequently pairs cloud-native tooling (AWS Bedrock, LangChain) with careful statistical practice, a combination that’s not obvious from job titles alone.
8 years of coding experience
6 years of employment as a software developer
Master of Science - MS Biomedical/Medical Engineering, Master of Science - MS Biomedical/Medical Engineering at San José State UniversityMaster of Arts - MA Medical Science, Master of Arts - MA Medical Science at Loyola University ChicagoBachelor of Science - BS Biology General, Bachelor of Science - BS Biology General at San Diego State University
Github Skills (10)
testing10
scikit-learn10
forecasting10
pandas10
machine-learning10
time-series10
forecast10
pytest10
python10
scikit10
Programming languages (3)
Github contributions (5)
sktime/sktime
Jan 2024 - Oct 2024
A unified framework for machine learning with time series
Role in this project:
Data Scientist
Data ScientistContributions:24 reviews, 11 PRs, 88 comments in 9 months
Contributions summary:Maxfield primarily contributed to the `sktime` repository, which focuses on machine learning with time series. Their work involved addressing deprecation warnings in the `EnsembleForecaster` related to `pd.DataFrame.groupby`, enhancing the `FallbackForecaster` by adding a `predict_interval()` option and a `nan_predict_policy`, and fixing a bug related to the `ExpandingCutoffSplitter`. The contributions demonstrate a focus on improving the robustness, functionality, and stability of the forecasting models within the library. Furthermore, the user added a new splitter to provide flexibility in time series analysis.
forecastingtime-series-analysistime-series-regressiondata-sciencedeep-learning
ninedigits/sktime
Jan 2024 - Oct 2024
Contributions:39 pushes, 10 branches in 9 months
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