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Posted September 17, 2026. The role appears to have been filled or removed. Check out similar open roles below.

Director, Data Science

Goremutualinsurance
Cambridge +1 more

Who this role is best for

Best suited to experienced data science leaders with a strong background in AI/ML and a strategic mindset, working in the insurance domain.

Best fit for

  • Experienced data science leaders with a track record in AI/ML and strategic roadmap development
    — “Conceptualize, design and execute an ambitious data science, ML and AI (e.g., LLM and agentic) roadmap”
  • Candidates who have led high-performing data science teams and delivered measurable business outcomes
    — “Lead a team of data scientists to develop, plan, and execute multiple analytical projects creating and delivering high quality AI and analytical solutions”
  • Individuals with expertise in model governance, validation, and ethical AI implementation
    — “Strategic direction on compliance for the design, development, and implementation of AI models into operational workflows”

Things to consider

  • The role demands a balance between technical rigor and business acumen for effective stakeholder communication
    — “Excellent communicator who is able to convey complex information in an understandable, compelling, and persuasive manner to non-technical clients and executives”
  • Candidates must be prepared to manage both production and non-production deployment environments
    — “overseeing 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”

How to stand out

  • Highlight experience in end-to-end AI/ML project lifecycle management and cross-functional collaboration
    — “Managing a data science project from end-to-end, including collaborating with partners and stakeholders”
  • Emphasize your ability to translate technical findings into strategic business recommendations
    — “Guide project teams in synthesizing analytical findings for consumption by internal analytical clients and business executives”
  • Showcase your leadership in model validation, governance, and ethical AI practices
    — “Design detailed validation plans and perform quantitative, conceptual and technical assessment of models”
  • Demonstrate experience in both technical execution and strategic planning for AI initiatives
    — “Creates the advanced analytics strategy, ensuring technology solutions comply with enterprise AI/ML standards”
  • Position yourself as a leader who can guide teams in balancing complexity with value in business problem-solving
    — “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”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • led a team of data scientists
  • developed predictive models
  • implemented AI/ML solutions
Typical background
PhD or Master's in Data Science, Statistics, or related field5+ years of experience in data science

Skills & requirements

Required

Data ScienceMachine LearningStatistical AnalysisTeam LeadershipProblem SolvingCommunication

Preferred

SQLPythonData EngineeringAi/ml

Stack & domain

SQLPythonVisualization MethodsData EngineeringInfrastructureAi/mlMachine LearningLLM WorkflowsAgentsSupervised LearningUnsupervised LearningData ScienceStatisticsProblem SolvingThought LeadershipCommunicationAgentic WorkflowsTeam LeadershipMentorshipStrategic ThinkingInnovationEmpirical StudiesExperimentationAnalytical RigorInsuranceAIMLAutomated DrivingFleet Operations

About the role

Original posting from Goremutualinsurance via Greenhouse

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.

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. This role will lead a team of data scientists focused on delivering measured value through AI/ML use cases that span across all aspects of Gore. 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. 

What will you do :

Model Development & Deployment 

Managing 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 

Developing and maintaining predictive models using advanced ML/AI techniques. Building Supervised and unsupervised learning models LLM workflows and agents. 

overseeing 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. 

Model Maintenance, Governance & Validation 

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.  

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. 

Leadership & Cross-Functional Collaboration 

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. 

Being 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. 

Advocates and advances 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. 

Driving change within 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.Excellent communicator who is able to convey complex information in an understandable, compelling, and persuasive manner to non-technical clients and executives and junior data scientists 

Strategy 

Creates 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. 

Research & Innovation 

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  

What skills will you need:

Minimum 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 

Over 10 years of expereince 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. Proficiency in building Supervised learning models [ (classification and regression) – tree-based (Random Forest, Stochastic Gradient Boosting and eXtreme Gradient Boosting, Decision Trees, Extra Trees, Regularized Greedy Forests), Generalized Linear Models, Discriminant models (LDA, MDA, FDA and QDA)], and Unsupervised learning models (Isolation Forest, Clustering algorithms),  Reinforcement learning, LLMs, agentic systems, graph and network analysis 

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.  

Proficiency in SQL, Python, Pandas, Numpy, Scikit-learn, TensorFlow, PyTorch etc.  

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 ideal candidate will have a passion for AI/ML and to foster a team of AI/ML and business experts and increase the data and analytics literacy with the business.  They have 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.

#LI-Hybrid

This posting pertains to an existing vacancy that is actively being filled.

Accessibility for applicants

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.

Source: Goremutualinsurance careers (Greenhouse)

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