- Built and managed a team of 5 Data Scientists/Machine Learning engineers.- Drive research & development projects in Programmatic Marketing including retargeting, look-a-like, product recommendations, CTR prediction, Bid pricing, and budgeting.

- Career coaching for IT professionals- Self-esteem and self-confidence coaching- Business coaching- Life coaching

Big US-based e-commerce client, Search team ● Led a team of 4 Data Scientists, communicated with the client, pre-sales, quarter/month projects planning.● Implemented two query classifiers using CNN on top of fasttext, which resulted in a 2% increase in revenue per visitor.● Implemented products ranking (pairwise approach using linear regression) inside solr, which resulted in a 3% increase in revenue per visitor.● Implemented recommendation system, next best filter model, query tagging (NER), statistical personalization model, features extraction from the image of the product.Technologies: python, keras, sklearn, pandas, numpy, spacy, gensim, mlflow, pyspark, databricks, git, github, jenkins, docker.Amazon Alexa’s skill (R&D NLP project)● Customer’s intent classifier using fastai ulmfit approach.● Customer’s query tagging (NER).Technologies: python, pytorch, tensorflow, fastai, pandas, numpy, keras, spacy, gensim, git, github, jenkins, docker, snowflake, datameer.

Miiix is an e-commerce B2B startup that solves the product matching problem for marketplaces.● Designed and implemented product matching algorithm (including image comparison using siamese neural network).● Designed and implemented search engine for products using gradient boosting algorithm and elasticsearch.Technologies: crf, ner, pandas, numpy, sklearn, xgboost, keras, flask, mysql, mongodb, elasticsearch, docker.

● Implemented churn prediction system of bank customers, AUC grew from 0.7 to 0.9.● Implemented the next best offer prediction model.Technologies: pandas, numpy, sklearn, xgboost.

Led a team of two actuaries, controlled full cycle of actuary department’s activity including reserving, pricing, segment analysis using best actuary practices and some machine learning algorithms (linear regression, generalized linear model).

Worked as part of a team of two actuaries, was engaged in pricing and reserving activities of the company.

Worked on pricing using generalized linear model and segment analysis of the company’s portfolio.