Senior Risk Analyst

  • 33314
  • Non-Life - Other
  • |
  • Ontario, Canada
  • |
  • Feb 8, 2018
Insurance
RESPONSIBILITIES
  • Provide general counsel, advice, and guidance on business and financial matters as required.
  • Maintain an accurate and complete trail of supporting documentation for all activities.
  • Ensure that all month-end financial duties and resulting financial reporting is completed in a timely and accurate manner.
  • Assist with preparation for any internal or external audits or independent reviews being conducted.
  • Analyze data and report on changing risk profile of the business.
  • Improve internal financial models.
  • Enhance and update models based on time-interval data to construct distributions of future credit risks.
  • Identify evaluate and implement new/ alternative data sources that can be used to enhance underwriting, collections or recovery processes.
  • Use statistical methods to analyze and predict credit risk to improve product pricing and underwriting of loan portfolio.
  • Build models to detect fraudulent activity.
  • Determine effectiveness of these programs by conducting pilots and developing measurements of success and implement monitoring.
  • Solutions must be practical and achievable within the constraints of the regulatory, systems and process environment.
  • Help automate monthly financial reporting processes to improve accuracy and efficiency.
QUALIFICATIONS
  • Degree in math, computer science, statistics, actuarial science or related field.
  • Three years of experience in the financial industry.
  • Ability to analyze and present numerical data in tables, spreadsheets, and forms.
  • Creative and curious.
  • Ability to read, understand, and calculate financial figures such as discounts, interest rates, proportions, percentages, and taxes.
  • Experience manipulating large volumes of unstructured data, and recognizing data quality.
  • Experience in statistical analysis techniques such as regression analysis, cluster techniques, including a good understanding of inappropriate interpretation of statistical results.
  • Familiar with open source statistical tools such as R and Python, and able to select best tool for the purpose.
  • Good at data visualization techniques to present complex information in clear manner to nontechnical audience.
  • Meticulous with numbers.
  • Proactive.
  • Ability to prioritize and manage conflicting demands.
  • High level of integrity and excellent work ethic.