Profilbild von Jacek Bajor Data Scientist, Machine Learning Engineer aus Berlin

Jacek Bajor


Letztes Update: 06.09.2022

Data Scientist, Machine Learning Engineer

Abschluss: M.Sc.Eng.
Stunden-/Tagessatz: anzeigen
Sprachkenntnisse: deutsch (Grundkenntnisse) | englisch (verhandlungssicher) | polnisch (Muttersprache)




Skilled data scientist and software developer proficient in machine learning with the background in computational medicine and medical imaging. Experienced in deep learning applications. Well versed in object-oriented programming languages, algorithms, and advanced data structures. Skilled in GNU/Linux administration. Eagerly explores new technologies, techniques, and trends in machine learning and software development.

Skills: Machine Learning, Deep Learning, Neural Networks, Object Recognition, Data Engineering, Data Visualization, Electronic Medical Records, Python (data science/machine learning stack including pytorch, tensorflow, pandas, sklearn, numpy, etc.), SQL, C, GNU/Linux, Docker


05/2019 - 12/2020
Senior Data Scientist/Machine Learning Engineer
Berlin Institute of Health
* Performed analysis and processing of large quantities of continuous patient data and
conducted research on predicting severe outcomes in the intensive care setting.
* Developed a recurrent neural network based model for predicting post-operative complications.

* Designed the software architecture incorporating the machine learning model.
* Led and conducted the development in accordance with processes for the product to
be certified under Medical Device Regulation.
* Integrated the product with the hospital's infrastructure and deployed it.
* Project was a part of the Digital Health Accelerator at Berlin Institute of Health in
collaboration with Deutsches Herzzentrum Berlin.

06/2018 - 03/2019
Data Engineer
Merantix/MX Healthcare
* Led the effort to build a vast dataset of medical mammography images in collaboration
with multiple healthcare sites in Europe.
* Anonymized and processed hundreds of thousands of images for use in a machine
learning project.
* Developed the backend for an online platform for X-ray image annotation.
* Participated in development of a convolutional neural network based deep learning
model for detecting and classifying abnormalities in mammography images.

11/2013 - 05/2018
Research Programmer
Vanderbilt University Medical Center
Department of Biomedical Informatics, Lasko Lab
* Conducted research on computational representation learning and its application to
electronic medical records [1].
* Developed supervised models using recurrent neural networks, noisy medical data to
predict multi-label targets [3,8].
* Designed and developed a web application for visualization of medical history employing
semantic embedding for medical concepts.
* Compared efficacy of different data formats and common predictive models for medical
outcome prediction [2].
* Implemented algorithms for statistical modeling in Python and C optimizing for speed
and API simplicity.
* Configured and maintained a GNU/Linux based computation server.

09/2012 - 11/2013
Software Developer
Center for Human Genetics Research
Center for Human Genetics Research
* Developed and maintained several web applications for human genetic research data
management and collaboration.
* Designed and developed mobile applications for iOS and Android including a computer
vision program for genetic sample management.
* Configured and maintained a GNU/Linux based web and database servers.

09/2011 - 09/2012
Research Assistant
University of Virginia
Department of Molecular Physiology and Biological Physics, Minor Lab
* Developed large structural biology oriented databases and web applications for research
collaboration and communicating results to the public [4,12].
* Configured and administered a network of highly utilized GNU/Linux based servers.
* Expanded the web-based laboratory information management system, by providing
unified data storage, improving data visualization and sharing capabilities in structural
genomics laboratories [4,10,11].
* Developed a high-throughput pattern recognition system, which automatically scans
images in search of protein crystals [13].

Zeitliche und räumliche Verfügbarkeit

Open to work in Berlin. Will be happy to travel for a project kick-off/meetings, but would prefer to work remotely if the job is outside Berlin. Happy to discuss details.



Profilbild von Jacek Bajor Data Scientist, Machine Learning Engineer aus Berlin Data Scientist, Machine Learning Engineer