Position: Data Scientist
Category: Data Science
English level: fluent
Years of experience: 2


Build several Data Science projects in areas:
NLP, Computer Vision, Recommender System, Predictive Modeling, Time Series

Proficient with tools and algorithms:
Deep Neural Networks, CNN, RNN, LSTM, linear regression, logistic regression, clustering, PCA, visualization

Perform:
Data Collection - can scrap using beautifulsoup/selenium/scrapy
Data Cleaning - Pandas, NumPy 
Feature Engineering - take a deep look into the data and come up with new useful features
Data Preparation - can take raw data and transform it so it can be fed to an ML model/Neural Network
Modeling - build ML models and Neural Networks using sklearn, Tensorflow, and Keras
Data Visualization - can visualize the data and complex relationships using python libraries matplotlib and seaborn

Deployment:
Can deploy the model to the web using Flask or dockerize it using Docker.
Expect to work with various Deep Learning/ML techniques, architect and build complex models using Tensorflow. Want to preprocess the data and train a model on it, evaluate and then deploy. Visualize the outcome and model's performance to the business side.
Don't want to:
Translate code from one language to another; Work with BI; Write too many reports - I'm productive when I work, not when I write reports all the time.