Data Scientist

Out-of-scope
Permanent, Full-Time

Work Location: Saskatchewan, Manitoba, Alberta, British Columbia, and Ontario. This role is eligible for in-office, hybrid, or remote work within the provinces where we operate. The successful candidate will be hired based on their current residence in one of these provinces.

Pay Range: $90,116 - $120,147
Posting Close Date: September 24, 2026

The Data Scientist is an analytics expert who uses their understanding of statistical models, machine learning algorithms, and scientific methods to extract insights from large amounts of structured and unstructured data to answer high-priority questions asked by the business and help them make data-driven decisions to deliver better products at SGI. This role applies data mining techniques, statistical analysis, and builds prediction systems integrated with these products. You will be expected to handle sensitive or confidential data in adherence to data governance standards and impact decisions at an executive level and use models to test the effectiveness of different courses of action.

You will create algorithms and run simulations to drive business results with data-based insights. Your primary focus will be creating predictive and prescriptive analytical models that allow the business to improve products and processes. These machine learning models will enable artificial intelligence within the business process to automate decision-making processes.

Key Accountabilities

Note: This section is not intended to be an exhaustive list of duties and responsibilities – other duties and responsibilities may be assigned.

Machine Learning/Predictive Modeling

• Works with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

• Liaises with lines of business and corporate functions on data science requirements.

• Develops a deep understanding of advanced analytics to identify, evaluate, and recommend data solutions that support evolving business strategies, operations, and processes.

• Mines and analyzes data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies.

• Uses predictive modeling to increase and optimize customer experiences, revenue generation, workflow decisions, and other business outcomes.

• Develops A/B testing framework to test model quality.

• Coordinates with different functional teams to implement models and monitor outcomes.

• Assists in the development of processes and tools to monitor and analyze model performance and data accuracy.

• Develops custom data models and algorithms to apply to data sets.

• Creates automated anomaly detection systems and tracks its performance.

• Identifies business applications of predictive analytics and artificial intelligence/machine learning, collaborates with stakeholders on the feasibility of such models, and provides support in model development and training.

• Conducts advanced analysis to proactively uncover new trends or perspectives on client data and provides findings to the business unit to assist with decision-making based on scientific thinking.

• Conducts complete advanced analytics project cycle from end to end: idea generation; framing the problem; identifying sources of data; selecting the methodology for the solution; and modeling, deploying, and monitoring the solution.

• Works with Business Insights and Analytics Report Development teams to identify, implement, and monitor the performance of predictive models to execute the business strategy.

Advanced Analytics Support

• Assists in the assessment of the effectiveness and accuracy of new data sources and data gathering techniques.

• Researches and tests third party sources of information that will improve the company’s data.

• Enhances data collection procedures to include information that is relevant for building analytics systems.

• Researches and evaluates data for the development, analysis, interpretation, and reporting of performance indicators, benchmarking, and opportunities for the business unit.

• Provides information in a clear, relevant format, such as a dashboard, graph, report, or presentation, to facilitate and support timely decision-making for operational areas through understanding business needs.

• Consults with Data Engineer to create and improve data assets and pipelines that improve the advanced analytics process.

Leadership

• Actively contributes to and supports a culture of high performing workforce.

• Participates in divisional succession plans, ensuring ongoing professional and career development and supports development in others.

• Supports a culture of leadership and accountability to effectively deliver on strategic and corporate strategies.

• Is actively committed to leadership development across the company, supporting team and workforce readiness through mentoring, training, and developmental opportunities.

Corporate Management

• Enables the success of programs and policies that are in alignment with corporate, strategic, and divisional strategies.

• Manages risk in area of authority.

• Ensures that the Health, Safety and Emergency Management Policy is applied in area of responsibility.

Education and Experience

• A four-year degree from an accredited post-secondary educational institution in a directly related field of study (e.g., Mathematics, Statistics, Engineering, Computer Science).

• Working towards or dedication to pursue designations and/or certifications in Data Science (e.g., Certified Specialist in Predictive Analytics [CSPA] designation from the Casualty Actuarial Institute or equivalent).

• Three to Five years of experience in a data science, research, and/or equivalent role.

• Three years of experience in Property and Casualty insurance with superior understanding of the business domain is an asset.

Knowledge, Skills and Abilities

• Knowledge of how to structure a data problem, from framing the right questions to ask, to communicating the results effectively.

• Knowledge of advanced machine learning algorithms and mathematical and statistical concepts and techniques (e.g., clustering, decision tree learning, artificial neural networks) and their real-world advantages and drawbacks.

• Knowledge of relational database structure.

• Skill in using common data science toolkits and statistical programming languages (e.g., R, Python, SAS, SQL) to manipulate data and draw meaningful insights from large datasets.

• Skill in processing high-level requirements from stakeholders to develop the required data extraction program and visualization needed for high-priority projects using industry standard reporting tools.

• Skill in gathering business requirements and transforming these into actionable data.

• Ability to visually present and communicate data, analyses, and findings.

Behavioural Competencies

Leader Level 3 – Applies (Team/Dept)

• Accountability - Provides Direction and Sets Expectations

• Business Acumen - Applies Broader Business Metrics and Understands the Internal and External Environment

• Change Agility - Makes Change Real for Others

• Leadership - Leads the Team

At SGI, we are committed to a workplace where people feel respected, valued, and able to contribute fully. Through fair, consistent, and transparent people practices, we attract skilled talent with varied lived experiences and offer meaningful work, opportunities for growth, and a strong sense of belonging. Our commitment to reconciliation includes inclusive hiring practices that create meaningful opportunities for Indigenous peoples and support a workforce reflective of the communities we serve. Join us in building a culture where contributions are valued and shared success is shaped by our people.  

If you require an accommodation during the recruitment process, we invite you to submit your accommodation request to [email protected] and we will work through your request with you. All information received will be kept confidential.

Posting Close Date: