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Data Anomaly Detection and Suggestions

Industry Financial Services, Hi-Tech

Specialization Or Business Function

Technical Function

Technology & Tools

CLOSED FOR BIDDING

Project Description

We are plannig to develop an unsupervised learning solution to detect anomalies in structured data.  Our data will be single tables only.  We need a solution that will detect anomalies across various data types (time series, configuration, etc.).  We need the solution to identify normalcy patterns in individual columns and in intercolumn relationships and then identify anomalies within those patterns and make suggestions for what a correct value could be (providing some confidence interval).

I realize the desrciption above is a bit generic but thats because we are looking to develop a base solution that works (to some level) in an unsupervised manner across a wide variet of data types.  We expect to need further tuning in order to maximize signal from different data types.

Stage 1: Planning (current project)

For this stage we are interested in finding data scientists with relevant background and experience in data anomaly detection similar to what is described above.  During this stage we will hire (pay) 1-3 data scientists to consult for one phone call on project planning and strategy.  Please apply to this project an explain why we should consult with you.

Stage 2: Execution (future project)

A future project posting will provide additional details, ask for proposals.  We will hire data scientist(s) to developer the solution.

Project Overview

  • Posted
    November 22, 2017
  • Preferred Location
    From anywhere
  • Payment Due
    Net 30

Client Overview


EXPERTISE REQUIRED

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