Alex Riley
Software Engineer at Wayve
United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolAlex Riley is a software engineer with 11 years of experience building data-intensive systems and machine learning infrastructure across healthcare and genomics startups. Currently on Wayve's Datasets team working in Embodied AI, he has previously led data pipeline and orchestration efforts at BenchSci, Healx and Congenica, migrating and scaling Python-based workflows into Airflow/Nextflow, Kubernetes and cloud-native environments. He brings deep practical expertise in pandas and scientific Python—evidenced by substantive contributions and bug fixes to the core pandas library and contributions to the popular "100 pandas puzzles" collection. Alex excels at translating research-grade algorithms into production pipelines for large biomedical datasets, having improved remote-file storage strategies and orchestrated hundreds of concurrent jobs to accelerate processing. With a Master’s in Mathematics and Philosophy, he combines analytical rigor with pragmatic engineering to improve observability, reliability and throughput for ML and data teams.
11 years of coding experience
10 years of employment as a software developer
Master’s Degree Mathematics and Philosophy, Master’s Degree Mathematics and Philosophy at University of Bristol
Stackoverflow
173,304reputation
17.0mreached
675answers
3questions
pandas
top-1%
floating-point
top-1%
regex
top-5%
profiling
top-5%
dictionary
top-1%
matplotlib
top-5%
Github Skills (58)
datetime10
matrix10
python10
data-science10
multidimensional-arrays10
data-mining10
pandas10
machine-learning10
vectorization10
math10
indexing10
10
numpy10
dataframe10
dictionary10
Programming languages (5)
Github contributions (5)
ajcr/100-pandas-puzzles
Nov 2015 - Sep 2020
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
Role in this project:
Data Scientist
Data ScientistContributions:1 review, 39 commits, 16 PRs in 4 years 10 months
Contributions summary:Alex primarily contributes to the project by adding and refining pandas puzzles focused on data analysis. Their commits involve creating and modifying Jupyter Notebooks containing puzzles and their solutions. The contributions span multiple sections and difficulty levels, demonstrating a focus on pandas fundamentals and data manipulation techniques. These tasks directly align with the repository's goals of providing exercises for pandas, numpy, and python skills in a data analysis context.
pandasnumpypythondata-analysis
pandas-dev/pandas
Jul 2015 - Sep 2015
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:Data Scientist
Data ScientistContributions:6 commits, 6 PRs, 22 comments in 2 months
Contributions summary:Alex primarily contributed to bug fixes and enhancements within the pandas library. Their work focused on addressing issues related to data types, particularly with datetime64, timedelta64, and string dtypes, ensuring correct behavior in functions like `pd.unique` and the DataFrame constructor. They also improved the `Series.ptp` function to correctly handle NaN values, demonstrating expertise in data manipulation and statistical analysis within the pandas ecosystem. Furthermore, the user made changes to improve indexing.
data-analysisdata-structuredata-structurespythonpandas
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