Position: Team Lead NLP & Machine learning engineer & Data Scientist
Category: Data Science
English level: fluent
Years of experience: 7

1) The company would like to predict energy consumption. I have built the ML- pipeline in GCP infrastructure with serverless architecture with high accuracy.
2) The company would like to identify if this transaction is Froud or not. I have built the model to predict financial Fraud using Graph models.
3) A stock exchange company collects and processes a lot of information in order to help their clients to make a decision. One type of data is business reports. Analytics generates a lot of business reports to help the decision-making process. In order to predict, how some events will be influenced key metrics of the company the report needs to be classified: as positive, negative, or neutral according to the aspect. I developed data science solutions to identify aspect-based sentiment. Moreover, I improved the prototype preprocessing model and got an increase in metrics 5 times. 
4) For clients need to parse the stock exchange websites and extract key values from tables and raw text. This information can help to identify the risk companies, or corruption and find relevant insights. I have implemented the data science solution pipeline for multilanguage approaches without training the model, using the question-answering model from BERT and TAPAS from Google. 
5) Solve the problem of extraction terms from financial documents. The main innovation is that the user needs to annotate just 5 examples of documents to train the model. After that, the model will be able to extract annotated terms on a new document with high accuracy.
Data Scientist with strong applied math background and great experience using predictive modeling, data processing, user segmentation, and data mining algorithms to solve challenging business problems. Passionate about deep reinforcement learning, natural language processing, and overcoming mediocrity. Has 6+ years of experience in Data Science.
Worked with different data, most of all with customers' behaviors. Experienced in eCommerce, Retail, Telecom, Public Sector, Dating, Finance, etc. Naturally identifies the real needs and opportunities of enterprises and thinks in terms of business and operational value. 
Have experience in engaging in the full cycle of understanding the business, gathering requirements, exploring the data, training, testing ML solutions, and finally, deploying them. Can work as Senior Data Scientist, Team or Tech lead.
- I prefer to be able to work remotely.
- I wish to have a challenging task where ML is applicable with enough data because AI needs data.
- I would not prefer to be micro-managed.