Machine Learning Engineer jobs in Canada

The Senior Data Analyst is an innovative and experienced analytics professional with hands-on expertise in all facets of data product development and a driving passion for turning business challenges and needs into game-changing data products.

Reporting to the Director, Data Leadership, the Senior Data Analyst will be an integral part of an innovative and dynamic team that translates business needs and opportunities into new data products for the business teams in Personal Insurance.

To thrive in this role, the Senior Data Analyst will need to have expert-level skills in exploratory data analysis and discovery using both SQL and Python, coupled with extensive experience with the ideation, design, and prototyping of scalable data products on cloud platforms. Experience with modern insurance processes, data visualization best practices, and geospatial analytics are also strong assets in this role.

What you’ll do:

• Analyze and evaluate new data sources based on current and future business requirement. Actively contribute to the design of new and innovative data products.

• Facilitate and participate in user story and requirement elaboration sessions with business and technical stakeholders, identifying both upstream and downstream functional and non-functional requirements. Oversee the documentation and translation of business needs into compelling user stories with clear business requirements and technical specifications.

• Support the product owner(s) with the product backlog and help to represent the customer to the Agile team. Work closely with Product Owner(s), delivery teams and business partners to deliver new and innovative data products and capabilities to business stakeholders.

• Contribute to project management activities such as scoping, impact assessments and estimating project efforts, identifying risks and recommending mitigation measures, communicating activity status as well as escalating and communicating possible issues.

• Participate in agile sprint ceremonies, daily stand-ups, sprint planning, sprint refinements and retrospective sessions.

• Working with business and engineering team on planning, documentation, and review of test case results for data products.

• Working with business stakeholders to ensure completeness of data documentation, monitoring of data integrity, and data governance.