Cyber360- ON-427

Desired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences, Mathematics, Statistics / Actuarial sciences
Company: Anonymous
Project Length: 6 months to 1 year
Preferred start date: 05/03/2021
Language requirement: English
Location(s): ON, Canada; Canada
No. of positions: 1-2
Preferred institutions: University of Ottawa, University of Toronto, University of Waterloo

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About the company: 

Our purpose is to build an analytics-driven organization by combining the latest techniques with deep industry, functional, and analytics expertise to help clients capture the most value from data.

Please describe the project.: 

With increase in attack surface, never before has cybersecurity presented such a complex challenge. While enterprises struggle with this growing IT complexity, they face two significant technology gaps when it comes to implementing effective security across their IT infrastructure: no holistic view across the entire organization, rather reinforcing operating silos; and no real-time actionable insight into where the security analyst must focus.

Cyber360 aims to address these shortcomings in today’s cybersecurity landscape by integrating security management systems with enterprise-wide risk management (ERM) framework, and by developing comprehensive, inside-out, scenario-based planning.

The main goal of the company is to develops decision support systems for financial services organizations using precision analytics. Our strategic solutions focus on Finance & Treasury, Operations, and Risk functions.

The main challenge to be addressed in Cyber360 is to develop a forward looking scenario-based Cyber risk management dashboard that integrates with the overall ERM framework. 

The candidate(s) will work with the Company’s experts to implement its proof-of-concept, develop back-end, front-end and microservices in line with our existing network architecture.

Required expertise/skills: 

Implementation of statistical techniques using Python, ML and database