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

Thomas Lautenschläger

nicht verfügbar bis 31.03.2023

Letztes Update: 30.11.2022

Machine Learning Scientist / Quant Analyst

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




  • Efficient and scalable implementation of computation intensive algorithms 
  • Time series analytics
  • Stock market analytics
  • Deep learning
  • Numerical stable implementations
  • Bayesian optimization
  • Optimization and analytics of high dimensional non-linear data 
  • Presentation, visualization and documentation of complex tasks, calculations in a comprehensible way
  • Process automation 
  • Verification of correct implementation of complex algorithms
  • Working in a research environment
  • Reinforcement learning (education in the research lab IAS Darmstadt @ TU Darmstadt)
  • Multi-armed bandits
  • Model predictive control
  • Probabilistic modelling
  • Up to date to current research
  • Feature extraction/creation
  • Clustering algorithms
  • Classification algorithms
  • Git / versioning
  • PyTorch
  • Numpy
  • Scikit-learn
  • SciPy
  • Pandas
  • Pyro
  • Stan
  • Python
  • FastAPI
  • Docker
  • Postgres
  • SQL
  • Tensorflow/ Tensorflow Probability
  • Terraform 
  • Google Cloud
  • Working as a quant analyst / machine learning scientist for a privately managed fund
  • Development of an analytics dashboard (django, flask, MongoDB)
  • Design and development of a relational database (PostreSQL) with access via API (fastAPI)
  • Build an automatized stock analytics algorithm that detects anomalies in real time and sends reports immediately (Never crashed since 1 1/2 years and consistent return rates) (PyTorch, Pandas)
  • Solved a non-linear optimization task using latest deep learning architectures for a research project to optimize the ideal setting of LED lamps given (Tensorflow, Matlab)
  • Working with robotics data and optimization/control using classic control algorithms or reinforcement learning methods
  • Twitter real-time sentiment analysis (spaCy)
  • Several data pipeline projects with distributed processing and data provisioning via Rest API access to the data lake and data warehouse (google cloud, fastAPI, docker, terraform)
  • Working mostly on projects with time series data.


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