Actuarial Consultant

at  KPMG

Overview:
At KPMG, you’ll join a team of diverse and dedicated problem solvers, connected by a common cause: turning insight into opportunity for clients and communities around the world.
To support its strong growth, KPMG is recruiting a number of professionals in the financial services sector. You will be involved in a variety of projects with clients exclusively in the financial services industry, including insurance companies and major Canadian banks.

Depending on your interests, you will work closely with partners and managers on engagements related to:

• quantitative modelling
• actuarial science

You are highly motivated and enthusiastic about taking on various challenges and working on projects of strategic importance. You have a strong ability to home in on key quantitative and qualitative concepts to develop value-added recommendations for our clients. You are a big-picture thinker and grasp new concepts quickly.

What you will do:

• Help carry out engagements regarding process reviews and optimization, strategic support and model reviews. Depending on your interests, engagements may cover the following types of activities:
• Quantitative and econometric modelling in the context of risk management
• Actuarial modeling using deterministic and stochastic methods by using various machine learning techniques
• Modeling within IFRS17 and IFRS9 context
• Development of tools and analytics in the actuarial context
• Financial risk management, including the metrics and models used and governance
• Support managers in drafting deliverables
• Quickly grasp concepts and issues that are key to meeting client needs and suggest potential solutions or areas for improvement
• Interact effectively with other team members and clients (internal and external)
• Support the team as needed on engagements involving fair value measurement of financial instruments (including derivatives), control and governance reviews or requiring quantitative analysis (including statistical factors)

What you bring to this role:

GENERAL QUALIFICATIONS

• Graduate diploma in finance, financial engineering, actuarial science, economics, financial economics or any related field, or a combination of a bachelor’s degree and a professional designation (CFA, FRM, ACIA, FCIA) or record of working towards a designation
• Minimum 2-4 years of experience in financial analysis, actuarial analysis, risk analysis, data science, statistical and quantitative modelling, or other similar relevant experience
• Understanding of how insurance companies and banks work
• Ability to clearly structure and summarize a number of concepts and make compelling recommendations
• Skilled at producing compelling presentations and reports
• Strong analytical and problem-solving skills
• Excellent communication skills.
• Sense of initiative and strong organizational and priority management skills
• Demonstrated ability to learn and succeed in a fast-paced, high-pressure environment
• Excellent teamwork and relationship-building skills
• A proven ability to handle a broad range of activities with competing priorities
• Highly disciplined and detail-oriented

SPECIFIC QUALIFICATIONS DEPENDING ON AREA OF INTEREST

• Quantitative modelling
• Knowledge of statistical and econometric modelling techniques (linear and logistic regression, time series, variable selection methods, Monte Carlo simulation, etc.)
• Knowledge of a programming language (Matlab, Python, R) (an asset)
• Strong ability to understand and model various interest rates
• Actuarial modeling
• Hands-on experience with actuarial modeling software AXIS or Prophet (an asset)
• Knowledge of data languages like SQL, VBA, SAS
• Knowledge of life/non-life and products
• Knowledge of IFRS9 or IFRS17

• Help carry out engagements regarding process reviews and optimization, strategic support and model reviews. Depending on your interests, engagements may cover the following types of activities:
• Quantitative and econometric modelling in the context of risk management
• Actuarial modeling using deterministic and stochastic methods by using various machine learning techniques
• Modeling within IFRS17 and IFRS9 context
• Development of tools and analytics in the actuarial context
• Financial risk management, including the metrics and models used and governance
• Support managers in drafting deliverables
• Quickly grasp concepts and issues that are key to meeting client needs and suggest potential solutions or areas for improvement
• Interact effectively with other team members and clients (internal and external)
• Support the team as needed on engagements involving fair value measurement of financial instruments (including derivatives), control and governance reviews or requiring quantitative analysis (including statistical factors