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