Roman S.

Data Scientist
  • New York City, USA
  • Member Since, Sep 15, 2019
Hire Roman S.
  • Industry Financial ServicesTech
  • Big Data Tools HadoopSpark
  • Specialties NLP

Candidte Description

Roman is a Data Scientist with over 8 years experience. His areas of expertise include NLP, Big Data and Image Processing with CNNs. He has worked on a range of projects, mostly related to digital marketing.

Education

  • St. Petersburg Polytechnic University 1991 - 1996

    MS in Computer Science

Experience

  • 2018 - Present

    Freelance Senior Data Scientist

    - Built predictive models for Li-ion and superconductors duty cycles with recurrent neural networks.

    - Carried out feasibility study for SSD and YOLO deep learning computer vision models.

    - Constructed massive geospatial data processing pipeline for employee vs customer classification.

    - Facilitated data engineering aspects of propensity models for major pharmaceutical retailer.

  • NYU Tandon School of Engineering 2018 - 2017

    Data Science Consultant

    - Developed course documents, code samples, and use cases for "Machine Learning in Finance" course.

    - Built a stock price prediction model from fundamental data using a recurrent neural network.

  • StepChange 2016 - 2018

    Data Scientist

    - Directed development of a user segmentation pipeline based on mobile historical records.

    - Built 95% accurate gesture recognition pipeline for wearable electronics.

    - Constructed a chatbot ecosystem intended for easy customization and customer data integration.

    - Analyzed a major European mobile network's profits/losses based on users' historical data.

    - Improved the churn model performance by 25% using mobile network social data.

  • Radiumone 2012 - 2016

    Data Scientist

    - Measured effectiveness of mobile ad campaigns using Hadoop, Hive and Python.

    - Built targeting segments for a major US airline with geo location.

    - Developed deep learning high cost media filtering system that reduced company's media expenses by 5%.

    - Architectured a distributed real time GPU-powered time series database.

    - Implemented a set of tools for processing and visualizing large geographical datasets (used C++, Cuda).

    - Developed predictive content classification pipeline that reduced classification costs by 90%.

    - Developed a model for social data sharing increasing performance by 100%+ for selected audiences.

Roman S. is now available for hire