Profilbild von Thomas Lautenschlaeger Machine Learning Scientist / Quant Analyst / Software Developer aus Darmstadt

Thomas Lautenschläger

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Letztes Update: 04.10.2023

Machine Learning Scientist / Quant Analyst / Software Developer

Abschluss: M.Sc. Computer Science - TU Darmstadt
Stunden-/Tagessatz: anzeigen
Sprachkenntnisse: deutsch (Muttersprache) | englisch (verhandlungssicher) | spanisch (Grundkenntnisse)




Core Competencies:
  • Efficient and scalable implementation of computationally intensive algorithms.
  • Expertise in time series and stock market analytics.
  • Proficiency in deep learning and numerical stability implementations.
  • Extensive experience with Bayesian optimization and high-dimensional non-linear data analytics.
  • Skilled in visualizing, presenting, and documenting complex tasks.
  • Strong background in process automation and verification of complex algorithm implementations.
  • Proven ability to thrive in a research environment.
  • Knowledgeable in reinforcement learning, studied at IAS Darmstadt @ TU Darmstadt.
  • Experienced in multi-armed bandits, model predictive control, and probabilistic modelling.
  • Up-to-date with current research trends.
  • Proficient in feature extraction/creation and application of clustering and classification algorithms.
  • Competent with Git/versioning systems.
  • Skilled in a variety of tools and frameworks, including AzurePyTorch, Numpy, Scikit-learn, SciPy, Pandas, Pyro, Stan, Python, FastAPI, Docker, Postgres, SQL, Tensorflow/ Tensorflow Probability, Terraform, and Google Cloud.

Professional Experience:
  • Quantitative Analyst/Machine Learning Scientist, Privately Managed Fund: Utilized machine learning techniques for fund management.
  • Developer, Analytics Dashboard: Developed an analytics dashboard using Django, Flask, and MongoDB.
  • Database Developer: Designed and developed a relational database (PostgreSQL) with API access via FastAPI.
  • Machine Learning Engineer: Built a robust stock analytics algorithm for real-time anomaly detection and reporting (PyTorch, Pandas).
  • Research Associate: Solved a non-linear optimization task using deep learning architectures for an LED lamp setting optimization project (Tensorflow, Matlab).
  • Robotics Data Scientist: Worked extensively with robotics data and implemented classic control and reinforcement learning algorithms.
  • Data Scientist, Twitter Sentiment Analysis: Conducted real-time sentiment analysis on Twitter data using spaCy.
  • Data Engineer, Multiple Projects: Developed several data pipelines with distributed processing and data provisioning via Rest API access (Google Cloud, FastAPI, Docker, Terraform).
  • Time Series Data Specialist: Led numerous projects involving time series data.


08/2022 - bis jetzt
Python Software Development - Machine Learning Engineering
(Energie, Wasser und Umwelt, >10.000 Mitarbeiter)

Dynamically scalable grid monitoring software for German electrical grid:
Working on conceptual design, implementation and go-live following DevOps best practices. 
Involves Machine Learning approaches and rule based mechanisms.

08/2023 - 03/2023
Developed an internal SDK for Data Scientist
(Energie, Wasser und Umwelt, >10.000 Mitarbeiter)

Development of a user-friendly Python SDK for accessing internal sensor data, tailored for data scientists. Implemented authentication processes in line with Azure standards.

02/2020 - 08/2022
Machine Learning Scientist/Engineer
(Banken und Finanzdienstleistungen, < 10 Mitarbeiter)

Design, development and evaluation of an investment software with backtesting/analysis functionalities that provide insights in the executed strategies. Moreover, the design of new strategies was part of this project.


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Profilbild von Thomas Lautenschlaeger Machine Learning Scientist / Quant Analyst / Software Developer aus Darmstadt Machine Learning Scientist / Quant Analyst / Software Developer