Position: Data scientist
Category: Data Science
English level: intermediate
Years of experience: 2

• Successful development of fraud-detection algorithms (supervised learning, fake company opinions);
• Participation in user segmentation, company segmentation projects (dimensionality reduction, t-sne, clustering);
• Conduction of data science trainings for teammates (python, supervised/unsupervised learning algorithms, visualization);
• Speaker at the DataFest workshop (http://datafest.in.ua/)
• 3+ years as Data Analyst, 1+ year as a Data Scientist
• Coursera / Udacity / Udemy certified
• UDS-club member: https://github.com/udsclub
• Active participant of DS events: AI Ukraine, AI Rush etc.
• Python: pandas, numpy, scikit-learn, matplotlib, Anaconda;
• Data retrieval / ETL: SQL / No-SQL, web-parsing, JSON, APIs
• Machine Learning: supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction, visualization), feature extraction / engineering - from linear models to xgboost
• NLP: n-grams, word embeddings (Hellinger PCA, word2vec, gloVe); stemming/lemmatization; sentiment analysis with NLTK, TextBlob, re, pandas
• Deep Learning: CNN, LSTM, keras, Tensorflow
• Solid Math background
I would like to apply my skills within these fields (R&D-based work is preferable): Data Science / Computer Vision / Machine Learning / Deep Learning.
I'm NOT INTERESTED AT ALL in: Banking, Telecom, eCommerce, Ad, Marketing, Gambling, Social/Media, Oil & Gas domains