Lars Jaeger

Data Scientist

https://talent.gravityer.com/lars-jaeger

Mercedes-Benz Tech Innovation GmbH

Key Strengths

Demonstrated interest in Data Science through personal projects like 'Time Series Anomaly Detection' and 'Optimize feed rations using LP'.
Experience with Python, a core language for Data Science.
Exposure to various programming paradigms and languages (Rust, C++, Java, Python) indicates adaptability.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's personal projects show a strong inclination towards self-learning and exploration across diverse technical domains. The current role as a Data Scientist at Mercedes-Benz Tech Innovation GmbH aligns with the target role, suggesting a good fit for a data-driven culture. However, the lack of detailed descriptions for experience and projects makes it difficult to fully assess collaboration and broader cultural alignment.

Soft Skills & Operational Fit

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

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

feed_optimization

May 12, 2026 – Present

Optimize feed rations using LP.

View Project

helix-debugpy

April 15, 2026 – Present

workaround for making helix work with debugpy

View Project

typed_polars

November 26, 2025 – November 26, 2025

A statically-typed wrapper around Polars for compile-time type safety

View Project

QuoVadisTAD

December 12, 2023 – May 14, 2024

Time Series Anomaly Detection

View Project

SudokuGenC

January 30, 2022 – February 14, 2022

SudokuGenC — GitHub repository

View Project

openPrecision

August 19, 2021 – October 4, 2024

openPrecision — GitHub repository

View Project

LarsJaeger

June 25, 2021 – December 18, 2025

Config files for my GitHub profile.

View Project

SpaceInvaders

November 12, 2020 – August 21, 2022

SpaceInvaders

View Project

primeNumberAlgorithms

November 5, 2020 – December 10, 2020

Trying out different algorithms to retrieve prime numbers.

View Project

Enigma

October 30, 2020 – November 4, 2020

Enigma — GitHub repository

View Project

Key Strengths

Demonstrated interest in Data Science through personal projects like 'Time Series Anomaly Detection' and 'Optimize feed rations using LP'.
Experience with Python, a core language for Data Science.
Exposure to various programming paradigms and languages (Rust, C++, Java, Python) indicates adaptability.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

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

Lars Jaeger

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit