Kyle Mylonakis

Data Scientist

https://talent.gravityer.com/kyle-mylonakis

Member since June 26, 2026

Key Strengths

Demonstrated interest in data science and machine learning through projects like 'GeoSeg', 'reinforcement_learning_tutorials', and 'Network-Comparisons'.
Proficiency in Python, a core language for Data Scientists, evidenced by numerous projects.
Experience with numerical methods and scientific computing (e.g., 'Finite-Element-Poisson-Solver', 'omega_equation', '1d-heat-transport').
Exposure to C++ and Matlab, indicating a versatile technical background.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and academic in nature, focusing on scientific computing and machine learning. While this demonstrates initiative and a passion for the field, there is no information on collaborative projects, team environments, or contributions to open-source, which makes it difficult to assess cultural fit for a typical team-oriented role. The projects align with a data scientist role, but the lack of professional experience or team-based work limits the assessment of cultural integration.

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

rust_tutorial

December 18, 2022 – December 18, 2022

A repository for working through the rust book.

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reinforcement_learning_tutorials

August 26, 2022 – September 14, 2022

Tutorials on reinforcement learning

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GeoSeg

August 30, 2018 – May 16, 2019

Implementations of various neural network architectures to infer the interface depth of simulations of the elastic wave equation with the frozen gaussian approximation.

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1d-heat-transport

August 2, 2018 – May 13, 2019

Investigating anomalous heat transport in one dimension.

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omega_equation

August 2, 2018 – August 2, 2018

This solves the Omega equation using GMRES to infer the vertical velocity of water in the quasigeostrophic approximation. The data is real world data gathered from the Santa Barbara channel.

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Network-Comparisons

February 13, 2018 – May 30, 2018

A package for easily testing different deep network block architectures

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Screen_Shot_Classifier

August 23, 2017 – March 26, 2018

Establish a datapipeline of screenshots from the top 100 Steam games for machine learning projects.

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Game-Picture-Classifier-Deprecated

August 11, 2017 – August 2, 2018

The backend for a planned website which can classify screenshots from Steam's top 100 most played games

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Cpp-examples-and-problem-solutions

July 24, 2017 – August 2, 2018

These are worked solutions to problems from almost all of learncpp.com and some worked out examples of parallel computing with MPI

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Finite-Element-Poisson-Solver

October 27, 2016 – October 27, 2016

Using Finite Element Methods to solve a two dimensional Poisson problem

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Key Strengths

Demonstrated interest in data science and machine learning through projects like 'GeoSeg', 'reinforcement_learning_tutorials', and 'Network-Comparisons'.
Proficiency in Python, a core language for Data Scientists, evidenced by numerous projects.
Experience with numerical methods and scientific computing (e.g., 'Finite-Element-Poisson-Solver', 'omega_equation', '1d-heat-transport').
Exposure to C++ and Matlab, indicating a versatile technical background.

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.

Kyle Mylonakis

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit