Shaurya Malik

Specialist at McKinsey & Company

New York, New York, United States
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Summary

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Senior
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Top School
Shaurya Malik is a data-focused software engineer and specialist with a decade of experience building data pipelines, ETL systems, and interactive visualizations across healthcare and industrial domains. Currently at McKinsey & Company after roles at Honeywell and UnitedHealth Group, he combines hands-on application engineering for human-machine interfaces with expertise in time-series exploration and Power BI-driven dashboards. He holds an MS in Data Science from Columbia University and a B.Tech from Manipal, blending academic rigor in intelligent systems with practical production experience. Known for translating complex data into clear, actionable insights, he has a track record of addressing privacy (data masking) and scalability in enterprise data warehouses. Colleagues describe him as equally comfortable prototyping research projects and shipping production-ready solutions, often drawing inspiration from medicine-driven applications of data science.
code10 years of coding experience
bookHigh School, High School at R. N. Podar School Mumbai
bookBachelor of Technology, Bachelor of Technology at Manipal Institute of Technology
bookMaster of Science - MS, Master of Science - MS at Columbia University in the City of New York
bookHigh School, High School at Campion School Mumbai
languagesHindi, English
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Stackoverflow

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Github Skills (16)

multi-task-learning7
hierarchical7
spring7
computer-vision6
natural-language-processing5
android5
kotlin5
nlp5
pytorch4
allennlp4
deep-learning3
bash3
machine-learning3
bert3
bookdown3

Programming languages (4)

RJavaScriptJupyter NotebookPython

Github contributions (5)

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shauryamalik/CrimesAnalysis

Mar 2021 - Apr 2021

Bookdown source files for EDAV final project
Contributions:1 review, 11 PRs, 56 pushes in 13 days
bookdownedavsource-files
shauryamalik/DataScience

Mar 2021 - Mar 2021

Material collected from various sources.
Contributions:39 pushes in 1 day
androidkotlinopenscienceanomalydetectionsources
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