Data Scientist

• Mar 2022 - Present

Data Scientist

• Jul 2021 - Feb 2022

1. Incidents analysis (POC). Exploring employee and workspace data to define features that are associated with the higher risk of incidents during the workday. 2. Recommender systems. Technical rewrite of the client’s solution, transfer to Azure Databricks platform. 1. Incidents analysis (POC). Exploring employee and workspace data to define features that are associated with the higher risk of incidents during the workday. 2. Recommender systems. Technical rewrite of the client’s solution, transfer to Azure Databricks platform.

Data Scientist

• Nov 2019 - Jun 2021

Building an automated recommender system for retail, combining together a number of various ml models in order to meet business objectives. Product recommendations: similar products, automated accessories generation, cross-sell, up-sell, products frequently bought together. Cold-start problem elimination. Utilizing all available product features. Personalized recommendations: relevant products/categories/promos/etc. for a user, next purchase prediction. Developing user deduplication model for providing relevant recommendations based on the whole user's activity data. Show less

Data Scientist

• Aug 2018 - Oct 2019

1. HR domain. Exploring employees data to define features that are associated with professional effectiveness. Creating BI system to monitor, compare and analyse employees. 2. Computer Vision domain. Developing a realtime webcam face recognition tool based on OpenCV libs. The tool defines unique faces, their age and gender, tracks emotions and builds an analytical dashboard. 3. Urban domain. Developing a visualization module based on Dash and Plotly. The module aims to provide daily human mobility analysis of different city zones using telecom data and show the most popular routes. 4. Agriculture domain. Building the yield forecasting model based on historical yield data, historical weather data, and protocols about crop favorable growing conditions. Creating Tableau BI system combining several datasources. 5. Healthcare domain. Exploring medical protocols and creating association rules based on symptoms, comorbid conditions and laboratory analysis for revealing diseases unnoticed by doctors. Creating LSTM model to predict patients next disease. 6. Automotive domain. Developing a part of the recommendation system based on statistical analysis (internship project). Responsibilities: • exploratory data analysis • data preprocessing • feature engineering • statistical analysis • visualization • machine learning models development Show less

Consulting Psychologist

• Apr 2013 - Jun 2018

School Psychologist

• Aug 2012 - Jul 2013