Henry Hinnefeld

Data Scientist

https://talent.gravityer.com/henry-hinnefeld

Member since June 19, 2026

Key Strengths

Demonstrated interest in data science and machine learning through personal projects like 'gitrisky' and 'terraingen'.
Proficiency in Python, a core language for Data Scientists, evident across multiple projects.
Experience with Jupyter Notebook, a common tool for data exploration and model development.
Exposure to web technologies (HTML, CSS, JavaScript) which can be beneficial for deploying data products or dashboards.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's personal projects show a strong inclination towards problem-solving and independent learning, which aligns well with an innovative and self-driven culture. The diversity of projects, from algorithmic trading to scientific instrument interfacing, suggests adaptability and a broad range of interests. The focus on Python and data-related tasks indicates a good fit for a data-centric role.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Projects

cta-alerts-git-scraper

November 16, 2022 – Present

cta-alerts-git-scraper — GitHub repository

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terraingen

December 5, 2020 – December 5, 2020

test using Houdini paired with Machine Learning to generate plausible terrain

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gitrisky

December 28, 2017 – Present

Predict code bug risk with git metadata

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brewlog

October 29, 2017 – December 8, 2022

web app for logging coffee brews

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alethiomoji

January 25, 2017 – November 25, 2020

An emoji golden compass

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evetrader

June 12, 2016 – September 10, 2016

System for algorithmic trading in EVE Online

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ppms

November 16, 2015 – September 9, 2019

Python code to interface with a Quantum Design PPMS DynaCool

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bibcheck.py

August 24, 2015 – August 27, 2015

A python class / command line utility to do automated literature searches with Google Scholar

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hinnefe2.github.io

July 27, 2015 – August 2, 2020

hinnefe2.github.io — GitHub repository

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keithley

July 1, 2015 – April 13, 2016

A class to interface with a Keithley 2400 sourcemeter

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Key Strengths

Demonstrated interest in data science and machine learning through personal projects like 'gitrisky' and 'terraingen'.
Proficiency in Python, a core language for Data Scientists, evident across multiple projects.
Experience with Jupyter Notebook, a common tool for data exploration and model development.
Exposure to web technologies (HTML, CSS, JavaScript) which can be beneficial for deploying data products or dashboards.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

Henry Hinnefeld

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit