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About the Role
This leadership position requires a unique combination of technical expertise, strategic thinking, and innovation to leverage data and advanced analytics solutions that drive business growth, enhance operational efficiency, and ensure regulatory compliance. You will lead and mentor a team of high performing data scientists and shape our growth strategy through empirical studies and experimentation. This role is resourceful, analytically rigorous, with extensive experience leading data science teams and a passion for solving product problems. This role is a mix of consulting know-how (problem solving, thought leadership, communication), analytical proficiency in statistics, data science and machine learning, agentic workflows, and, when required, hands-on proficiency in SQL/Python programming, visualization methods and technologies, and data engineering / infrastructure. This role is responsible for leveraging data science to assess risks, improve underwriting, detect fraud, and optimize pricing models while unlocking valuable insights, optimize processes, and inform decision-making. By implementing advanced analytics and ensuring data integrity, this role enables the organization to make informed decisions, streamline operations, and ultimately provide better coverage and services to policyholders while managing risks effectively.
Responsibilities
- Manage a data science project from end-to-end, including collaborating with partners and stakeholders to understand the business problem, obtaining data, defining an experimental design, setting up a model building pipeline, overseeing a team of data scientists to build necessary models, and working with a team of developers to implement models and managing a monitoring process.
- Develop and maintain predictive models using advanced ML/AI techniques, including Supervised and unsupervised learning models, LLM workflows, and agents.
- Oversee the development of analytical products and machine learning models, AI models, LLM workflows and agents, building and enabling analytics infrastructure including production model deployment, as well as Non Prod experimentation, deployment and testing.
- Define metrics to measure the impact of AI initiatives on business outcomes.
- Design detailed validation plans and perform quantitative, conceptual and technical assessment of models; Discuss and effectively communicate validation observations and findings with teams.
- Accountable for the integration of AI solutions, application deployment in production including, app health, resiliency, performance, security, enterprise data management standards, ethical and privacy standards.
- Continuously monitor and improve the performance of AI models, ensuring their accuracy, reliability, scalability, and ethical application. Includes optimization of our end-to-end machine learning pipelines, scaling, automating, and monitoring our predictive models and pipelines.
- Provide strategic direction on compliance for the design, development, and implementation of AI models into operational workflows, including helping draft and review the procedures that support a compliance system. Responsibilities include guiding AI teams with project planning, system architecture, risk management, verification & validation, and continuous monitoring.
- Lead a team of data scientists to develop, plan, and execute multiple analytical projects creating and delivering high quality AI and analytical solutions across a broad spectrum of projects and business lines.
- Act as a change champion and help the business conduct business problem opportunities and assessment identifying revenue generation and cost saving opportunities, developing proposals and make recommendations for model usage to the downstream partners.
- Advocate and advance modern, Agile solution delivery practices, great design, engineering and organizational practices, challenging the team to utilize creative thinking to modify or select the most suitable procedure/approach to solve a business problem balancing complexity and value.
- Drive change within the team and across broader Data & Analytics the importance of learning our business and the respective to help aid in our building the best solutions – be a business expert.
- Guide project teams in synthesizing analytical findings for consumption by internal analytical clients and business executives.
- Create the advanced analytics strategy, ensuring technology solutions comply with enterprise AI/ML standards, model governance and model risk standards, and AI Ethics, Fairness and Bias related control practices.
- Conceptualize, design and execute an ambitious data science, ML and AI (e.g., LLM and agentic) roadmap.
- Own the business outcomes, KPIs and deliverables of that roadmap working across stakeholders.
- Identify and define new strategic ML opportunities and work with cross functional teams to understand business requirements and guide the team to provide data-driven solutions, improving how we do data collection, storage, experimentation and analysis.
- Stay current with the latest advancements in Agentic/AI/ML solutions and evaluate their applicability to Gore.
- Develop strategic relationships and partnerships with the startup, academia, and industry ecosystem to garner mindshare and learnings.
- Foster a culture of innovation by encouraging research, experimentation and exploration of novel AI techniques.
Requirements
- Over 10 years of experience with a minimum 8 years of relevant professional experience.
- 4+ years of leading a team in developing and implementing AI/ML solutions (predictive, prescriptive, ML etc.) with an excellent understanding of the underlying Statistical, Machine Learning theory, and Predictive Modeling Lifecycle.
- Extensive experience in building, deploying, and managing production-ready generative models and machine learning models.
- Foundational and applied knowledge of statistical analyses, data science, and machine learning including, but not limited to descriptive, inferential, or causal statistics, predictive and forecast modeling, optimization modeling, NLP, LLM and agentic workflows and A/B testing methods.
- Deep expertise in developing and maintaining predictive models using advanced ML/AI techniques.
- Deep knowledge and hands-on experience in Machine Learning, Data Science, and AgenticAI, including experience with MLOps to build end-to-end pipelines and deploy models in production.
- Experience in building Deep neural networks (MLP, CNN, RNN, GRUs, and LSTMs) and use of AI/Deep Learning frameworks like TensorFlow, PyTorch, CNTK, and Keras.
- Experience with cloud platforms such as AWS, Google Cloud, or Azure.
- Excellent problem-solving skills, strategic thinking, and a proactive approach to challenges.
- Exceptional communication skills, with the ability to explain complex concepts to a non-technical audience and influence top-tier executives.
- Proven ability to translate complex data findings into actionable business strategies and drive business growth.
- Deep understanding of the complexities and tradeoffs of leveraging/deploying ML/AI at scale.
- An analytical mindset, be a self-starter, comfortable with ambiguity, detail oriented and have desire to work in a fast-paced, cross-functional environment while influencing business performance through insights.
Skills
- Statistics
- Data Science
- Machine Learning
- Agentic workflows
- SQL
- Python programming
- Visualization methods and technologies
- Data engineering
- Infrastructure
- Supervised learning
- Unsupervised learning
- LLM workflows
- Agents
- MLOps
- Deep neural networks (MLP, CNN, RNN, GRUs, and LSTMs)
- TensorFlow
- PyTorch
- CNTK
- Keras
- AWS
- Google Cloud
- Azure
- Pandas
- Numpy
- Scikit-learn
Location
- Ontario
- Western Canada
Work Type
- Hybrid
Experience Level
- 10+ years of experience
- 8+ years of relevant professional experience
- 4+ years of leading a team
Education Level
- Master's degree
- Ph.D. highly preferred in a technology/analytical field such as Computer Science, Physics, Economics, Data Science, Operations Research, Machine Learning, Engineering, or other relevant scientific fields
About the Company
- At Gore Mutual, we’ve always set ourselves apart as a modern mutual that does good. Now, we’re proudly building on that legacy to transform our company—and our industry—for the better.
- Effective January 1, 2026, Gore has joined Beneva—the country’s largest mutual insurance company—as part of its Property & Casualty operations in Ontario and Western Canada. During 2026, Gore will combine its operations with Unica Insurance, Beneva’s Ontario-based subsidiary specializing in niche commercial and personal insurance, creating a stronger, more diversified mutual insurer with greater scale and long-term stability.
- Every decision and investment remains anchored in long-term benefits to customers, members, and communities. Come join us.
Equal Opportunity
- Gore Mutual Insurance Company is committed to providing accommodations for people with disabilities during all phases of the recruiting process, including the application process.
- If you require accommodation because of a disability, we will work with you to meet your needs. Contact us and a human resources representative will consult with you to determine an appropriate accommodation.
- Should you request an accommodation during the interview process, please notify your Talent Acquisition Consultant.