Senior R&D Actuary

Do you have a passion for transforming complex data into actionable insights? Join our team where your actuarial expertise will directly impact business decisions across North America. This role offers you the opportunity to be at the intersection of traditional actuarial science and cutting-edge analytical techniques, helping shape the future of life insurance risk assessment.

About the Role

As a Senior Research & Development (R&D) Actuary, you'll be instrumental in developing and maintaining sophisticated mortality and lapse assumptions that drive our business decisions. You'll leverage your analytical prowess to translate experience data into valuable insights that inform product development, pricing strategies, and portfolio management across both Canadian and US markets.

Key Responsibilities

• Lead experience analysis initiatives to monitor population and insured life trends across direct insurance and reinsurance portfolios
• Develop key assumptions for mortality and lapse rates used in new business costing, in-force management opportunities, and business valuation
• Analyze complex data sets to identify underlying drivers of mortality and lapse, including policyholder behavior, product characteristics, and underwriting methods
• Create innovative tools and analytics to enhance monitoring methods and improve assumption accuracy
• Stay current with industry research and publications to continuously refine our methodologies
• Collaborate cross-functionally with Canadian and US market units, Risk Management, In-force Optimization, and Portfolio Steering & Monitoring teams
• Present findings internally to educate colleagues and externally to clients, potentially at industry events and special client meetings
• Document thoroughly all assumption development processes in compliance with corporate governance standards
• Ensure alignment between developed assumptions and their implementation in models to prevent unexpected errors

About the Team

The Actuarial and Research Development team specializes in life insurance experience monitoring/analysis and assumption development support for both Canadian and US markets. Our team leads and ensures consistent application of sound actuarial principles, methods, and tools across the organization. We provide critical insights that drive product development, pricing strategies, and experience analysis.

About You

You're a detail-oriented professional who thrives on solving complex problems and communicating technical concepts clearly to diverse audiences. You have a curious mindset that drives you to continuously improve methodologies and challenge conventional thinking. You're comfortable working with ambiguity and can balance multiple perspectives when making recommendations.

We are looking for candidates who meet these requirements:

• Fellowship with the Society of Actuaries with 7+ years of relevant experience
• Bachelor's degree in mathematics, statistics, actuarial science, or related field with demonstrated mathematical and analytical abilities
• Experience in mortality and lapse assumption development for life insurance products
• Proven ability to translate complex analytical findings into clear business recommendations
• Strong communication skills with the ability to present effectively to various stakeholders

These are additional nice to haves:

• Experience with advanced analytical techniques (GLMs, machine learning, AI)
• Proficiency in technical tools such as Excel, Visual Basic, R, Python, SAS, or AXIS
• Knowledge of actuarial modeling platforms like ICE or Stargate
• Experience working in both Canadian and US insurance markets
• Demonstrated ability to influence without authority in cross-functional teams
• Creative problem-solving approach and resourcefulness in overcoming barriers
• Experience presenting at industry events or client meetings

The base salary hiring range for this existing position located in Toronto is CAD $156,000 to $195,000. The specific base salary offered for this or any given role will take into account a number of factors including but not limited to job location, scope of role, qualifications, complexity/specialization/scarcity of talent, experience, education, and employer budget. At Swiss Re, we take a "total compensation approach" when making compensation decisions. This means that we consider all components of compensation in their totality (such as base pay, short-and long-term incentives, and benefits offered), in setting individual compensation.

About Swiss Re

Swiss Re is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.

Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.

If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience.

We may use AI-powered tools to support the review and evaluation of applications for this position. These tools provide additional insights to our recruitment teams, but all hiring decisions are carefully reviewed and made by people. To learn more about how we use AI in recruitment and how we handle your personal data, please review our Data Privacy Statement before applying.

Keywords:
Reference Code: 137734