Dmitry Efimov

New York City Metropolitan Area Contact Info
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Machine learning engineering leader with 15+ years of experience in solving different…

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Experience & Education

  • Amazon

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Patents

Honors & Awards

  • 2nd Prize of the Cervical Cancer Screening competition

    Genentech

    The goal of this competition was to predict which women will not be screened for cervical cancer on the recommended schedule. Identifying at-risk populations will make education and other intervention efforts more effective, ideally ultimately reducing the number of women who die from this disease.

  • 3rd Prize of the Western Australia Rental Prices competition

    Deloitte

    The goal of this competition was to improve on existing models by accurately estimating the weekly market rental value for residential properties across Western Australia.

  • 2nd Prize of the West Nile Virus Prediction contest

    Chicago Department of Public Health

    Given weather, location, testing, and spraying data, this competition asked to predict when and where different species of mosquitos would test positive for West Nile virus. A more accurate method of predicting outbreaks of West Nile virus in mosquitos will help the City of Chicago and CPHD more efficiently and effectively allocate resources towards preventing transmission of this potentially deadly virus.

  • 1st Prize of the Risky Business competition

    American Express

    The purpose was to improve credit risk models by predicting the probability of default on a consumer credit product in the next 18 months. More accurate credit risk evaluations allow issuers of credit to be able to responsibly extend and manage credit lines for their customers. The goal of this contest was to make the most accurate ranking of customers' credit risk given key data related to customer behavior.

  • 2nd Prize of the As the World Churns competition

    Deloitte

    The purpose was to predict which customers will leave an insurance company in the next 12 months: http://www.kaggle.com/c/deloitte-churn-prediction

  • 3rd Prize of the Amazon.com - Employee Access Challenge

    Amazon.com, Kaggle

    The objective of this competition was to build a model, learned using historical data, that would determine an employee's access needs, such that manual access transactions (grants and revokes) are minimized as the employee's attributes change over time. The model takes an employee's role information and a resource code and returns whether or not access should be granted.
    Our solution is posted here: https://github.com/diefimov/amazon_employee_access_2013

  • 2nd Prize of the KDD Cup Track 1 - Author - Paper Identification Challenge

    KDD, Kaggle

    The goal of the Author-Paper Identification Challenge was to predict whether an author has written a paper assigned to them in the Microsoft Academic Search database.

  • 2nd Prize of the Predicting the Strength of Social Ties competition

    PanjiaCo

    The purpose of this competition was to create a predictive modeling system that can use a set of data about people to compute the most accurate predictions of self reported connection strengths between any two nodes. The data that must be analyzed to create these scores comes from Facebook, LinkedIn, Gmail, and Public Records.

Languages

  • English

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Organizations

  • American Mathematical Society

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