Data Scientist

THE EMPIRE LIFE INS. CO•Kingston, ON

5d•CA$104,041 - CA$153,690•Remote

About The Position

Empire Life is looking to hire a Data Scientist to join our Data and Analytics team! We are actively seeking candidates to fill a current, open position. The Data Scientist will play a pivotal role in supporting the design, development, and deployment of advanced analytics, machine learning, and Generative AI solutions that drive measurable business value through predictive analytics, intelligent automation, and AI-assisted decision systems. The Data Scientist will be involved in a combination of traditional data science initiatives and modern AI applications, including predictive modeling, LLM-powered solutions, intelligent automation, and AI-assisted decision support systems. This position operates within a modern enterprise AI ecosystem leveraging Microsoft Azure, Snowflake, and other enterprise AI platforms to deliver scalable and governed AI solutions. This role reports to the Director of Data and AI strategy.

Requirements

Master's degree or higher, in a quantitative field such as Statistics, Mathematics, Computer Science, or Engineering.
2+ years of working experience in a quantitative role, ideally in data science and machine learning field
Strong programming skills in Python and SQL, with a deep understanding of both traditional machine learning concepts and Generative AI concepts and algorithms, including experience with Azure OpenAI and Google for Generative AI.
Experience with applied statistics and quantitative modelling (e.g. regression, segmentation, experimentation)
Ability to translate ambiguous business problems into measurable analytical and AI-driven solutions.
Ability to communicate analytical insights, AI limitations, and solution recommendations to both technical and non-technical stakeholders.
Experience supporting enterprise AI or intelligent automation initiatives
Familiarity with AI governance, model risk management, or responsible AI practices
Familiarity with conversational AI, intelligent document processing, or knowledge assistant solutions
Exposure to document intelligence, knowledge assistants, semantic search, or enterprise AI copilots
Experience working in agile product delivery environments
If you are applying for a position which is open to applicants across Canada, unless otherwise indicated in the position, language proficiency in English is required for communicating with customers, advisors, or employees across Canada.

Nice To Haves

Experience within insurance or financial services environments is strongly preferred
Experience with modern machine learning and AI techniques, including deep learning, Generative AI, large language models (LLMs), retrieval-augmented generation (RAG), or agentic AI systems is considered an asset.
Familiarity with LLM evaluation approaches, prompt optimization, semantic retrieval systems, and AI-assisted workflow design is considered an asset.

Responsibilities

Participate in the development and implementation of both traditional machine learning and Generative AI initiatives that drive business value, leveraging enterprise platforms including Microsoft Azure AI services, Snowflake, OpenAI technologies, and approved enterprise AI tooling
Partner with business stakeholders, technology teams, and product owners to identify opportunities for analytics, AI, and intelligent automation solutions
Evaluate machine learning and Generative AI systems using quantitative metrics, experimentation methodologies, human evaluation techniques, and business outcome measurements.
Translate complex business problems into analytical and AI-driven solutions that support operational efficiency, customer experience, risk management, and business growth
Develop and evaluate machine learning and statistical models using techniques such as classification, regression, clustering, forecasting, optimization, experimentation, and deep learning
Develop and evaluate Generative AI applications including retrieval-augmented generation (RAG), semantic search, intelligent assistants, prompt engineering, and orchestration-based AI workflows.
Perform exploratory analysis, feature engineering, experimentation, model evaluation, and visualization to support data-driven decision making
Support responsible AI practices including model explainability, governance, monitoring, and compliance requirements
Collaborate with ML Engineering teams to transition models and AI capabilities into scalable enterprise solutions

Benefits

Hybrid work model
Competitive salaries with annual pay increases
Annual bonus program, which recognizes both strong company performance and individual contributions, for non sales positions
Access to learning & development programs, and education/tuition reimbursement (role dependent), to support your professional growth and career advancement.
Competitive uncapped commission, for sales positions
A comprehensive employer-funded benefits package starting from day one of employment, that includes life insurance, health and dental and a generous health account
Flexible work arrangements and an annual allotment of personal health days.
Four weeks annual vacation from hire date
A defined contribution pension plan with generous employer matching
Top up programs for parental leave and compassionate leave
Employer-sponsored wellness and recognition programs
A cash employee referral program