Position: Data Scientist/ML Engineer
Category: Data Science
English level: upper
Years of experience: 0.5

Projects:
Steel defect detection (cv2, keras, pytorch)

Forest fires influence analysis (data mining and analysis, time series processing and analysis)

Character recognition using PCA (cv2, linear algebra)

Reinforcement learning course by SoftServe
I am a 4-year Computer Science student at Ukrainian Catholic University.  Here I`ve developed strong, soft skills as I was usually working in a team. I`m communicative, attentive to details, hardworking. I have tried myself in such fields of Computer Science: cybersecurity, web development (both front and back end), embedded, and now I`m hardly developing myself in AI sphere.

Working experience:
7 month as Python Engineer
3 month as ML Engineer

I had experience in such AI fields as:
- supervised/unsupervised learning: linear and logistic regression, SVM, decision trees, classifiers

- Deep learning: image classification and segmentation (keras & pytorch)

- Reinforcement learning: basics of DQN, Policy gradients, A2C, MCTS

- Time series forecasting: ARIMA models, differencing and decomposing of ts, predicting future profit

- Computer vision: image stitching, recognition, classification and segmentation

- NLP: authorship detection, sentence similarity, toxicity classification

On my last job, I was creating a recommendation system. I was responsible for data processing and visualization, feature engineering using statistical methods and some state-of-the-art techniques as TF feature columns. Also,  I was involved in the deployment of the model using TF Extended.
I'm expecting precise requirements and rules, friendly team, which are in passion of what are doing.