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Data Scientist/Analyst – Fraud Detection – Level 2

October 19, 2020 by

Job Posting Title: Data Scientist/Analyst – Fraud Detection – Level 2
Location: Toronto, ON
Duration: 5 months

Our public sector client is looking for a Data Scientist/Analyst (L2) resource to:

·      Work with various business areas of the Ministry to support BIBA efforts in understanding and consolidating the Program/Business requirements for fraud/anomaly detection

·      Draft a Business Case proposal for a project to address Fraud Detection requirements for the Ministry.

·      Perform detailed analysis and determine the suitability of data science methodologies and tools as well as propose potential technical solutions

·      Understand short from long term business objectives and come up with a roadmap

·      Review various datasets available in terms of their suitability, and where gaps are found, suggest what other data might be needed to resolve specific problems.

·      Propose technical solutions which may include developed in-house as well as off-the-shelf commercial products

·      Develop a proof of concept to illustrate the technical solutions proposed

·      Develop benchmarking tests for comparing various solutions proposed by external vendors

·      Document the solutions proposed and organize workshops with business and IT teams and forge collaboration with stakeholders.

·      Perform formal knowledge transfer for any solutions proposed

·       Develop a proof of concept to illustrate the technical solutions proposed
 

The required skills for the Data Scientist/Analyst L2 are:

·      Experience dealing with financial transactions in fraud detection techniques (ideally in a pay per claim model)

·      Familiarity with fraud detection technics (rule-based, statistical/predictive models, AI) and software tools

·      Strong business and data analysis skills

·      Have solution designing experience in Fraud Detection platform setup including infrastructure and software

·      Experience designing and building predictive models with both traditional data mining as well as modern machine learning/AI algorithms

·      Familiarity with one or more AI toolkits (ex.TensorFlow, Torch, Keras)

·      Expertise in open-source data science tools (preferably python)

·      Experience in operationalizing predictive models

·      Communication and presentation skills

 

Ideal resource would have experience with:

·      Financial data related to health-related services

·      Processing financial claims (insurance industry)

·      Home grown and/or commercial solutions for fraud detection

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