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

Jacek Bajor

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Letztes Update: 06.09.2022

Data Scientist, Machine Learning Engineer

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

Dateianlagen

jacek_bajor_cv.pdf

Skills

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

Projekthistorie

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.

Kontaktformular

Kontaktinformationen

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