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Location: Brazil
Remote: Yes, or Hybrid or Office
Willing to relocate: Yes
Technologies: Data Science, Machine Learning (ML), Deep Learning (DL), Computer Vision (CV). Geospational data and IoT sensors (weather and environmental), satellite images, gridded/array data and time-series
Résumé/CV: https://www.linkedin.com/in/ilirium/
Email: [kalimulin.jbs] located in the [gmail.com] service
Result-oriented Data Scientist with PhD and broad experience with machine/deep learning (ML & DL) and data science in fields of computer vision, geospatial & climate data (4+ years), and as a Research Fellow in Microwave CAD/EDA (7 years). Solid software engineering skills and mindset. I use satellite images, radar data, and time-series structured data in my work projects.Key results related to hard skills: – Create, train and tune CNN/RNN models (classification and segmentation tasks) – Statistical processing and data analytics of times series from IoT sensors and satellite images – Remote sensing and computer vision: georeferencing, warping, image filtering and processing, object recognition, interpolation – Benchmarking and speed up: async, threads, multiprocessing, multidimensional array algorithms with Numpy – Developed backends for data analyzing services and prediction API in Python and Golang – Dashboard for comparing data sources by different statistic metrics – Deployed services to production and staging with Docker Compose, GitLab CI/CD and Bash Key results related to soft skills: – Wide experience of remote work, also before the lockdown – Defended a Ph.D. degree on time – Presented research results on scientific conferences (more than 20) – Retrained myself from a research fellow in the CAD/EDA industry to the data scientist in IT Main tech stack: Python and Golang, Numpy, Pandas, SciPy, Scikit-learn, PyTorch, OpenCV, Pillow, Git, Bash, Jupyter, PyCharm, Docker, GDAL, PROJ, QGIS, GeoTIFF, HDF5. |