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Canada Goose

Data Scientist

Posted 17 Days Ago
Be an Early Applicant
In-Office
Toronto, ON
Junior
In-Office
Toronto, ON
Junior
The Data Scientist analyzes complex datasets, develops predictive models, collaborates with teams to drive data-informed decisions, and creates compelling visualizations.
The summary above was generated by AI

Location:

Toronto

Address:

100 Queens Quay East Toronto, Ontario M5E 1V3 Canada

Job Title:

Data Scientist

Canada Goose isn't like anything else. We've built something great, something special - an iconic lifestyle brand with an inspirational and authentic story. At the heart of it is our promise to inspire and enable all people to thrive in the world outside. To Live in the Open. At Canada Goose, you're part of a movement that belongs to something bigger. One that seeks out the restorative power of nature and is driven by a purpose to keep the planet cold and the people on it warm. We endure any condition, observe every detail, and are building a community that believes in living bravely and coming together to support game-changing people.

Here, opportunities are everywhere - to try something new, to learn, to do meaningful and impactful work, and they're yours for the taking.

Position Overview:

The Data Scientist is a critical contributor to unlocking insights and driving data-informed decisions across Canada Goose. In this role, you will design, develop, and deploy advanced analytics and machine learning solutions, ensuring the accuracy, integrity, and value of corporate data. Through collaboration with data analysts, data engineers, vendors, and key business stakeholders, you will translate complex data into actionable recommendations that enable digital transformation, operational efficiency, and strategic growth.

What You'll Do:

  • Data Analysis & Insights: Analyze large, complex datasets to uncover trends, patterns, and actionable insights that drive business decision-making.
  • Model Development: Design, build, and validate predictive models and machine learning algorithms to solve real-world business challenges.
  • KPIs & Metrics: Design and develop business metrics to measure and drive performance across various domains, including customer value (e.g., CLTV – customer lifetime value), marketing effectiveness (e.g., Marketing Mix Modeling, Multi-Touch Attribution), financial performance (e.g., profitability metrics, IRR – Internal Rate of Return, NPV – Net Present Value).
  • Data Pipeline Engineering: Develop and maintain robust data pipelines for the collection, processing, and transformation of structured and unstructured data.
  • Collaboration: Partner closely with stakeholders across business, technology, and analytics teams to understand requirements and develop data-driven solutions.
  • Data Visualization: Create clear, compelling visualizations and dashboards to communicate findings and performance metrics to both technical and non-technical audiences.
  • Data Governance & Quality: Ensure data integrity, accuracy, and compliance with organizational standards and regulatory requirements.
  • Continuous Improvement: Monitor and refine deployed models to ensure accuracy and relevance, proactively identifying opportunities for increased efficiency and performance.
  • Documentation: Maintain comprehensive documentation of data sources, analytical methods, and model assumptions to support transparency and reproducibility.
  • Innovation: Stay current with emerging data science techniques, tools, and best practices, championing the adoption of new technologies and approaches within the team.

Let's Talk About You:

  • 1-3 years of proven experience in Data Science, Analytics, or AI initiatives, including managing vendor-driven projects and teams.
  • Strong knowledge of Statistics and expertise in statistical analysis models and methodologies.
  • Deep expertise in Python, PySpark, R, SQL and related programming languages and libraries.
  • Hands-on experience with Power BI, or Tableau for dashboard development and story telling.
  • Knowledge of Azure Data & Analytics services, such as Azure Fabric Data Warehousing, Data Factory, Cosmos DB, and related tools.
  • Experience with cloud platforms, APIs, and modern integration solutions.
  • Experience in Microsoft Fabric, Databricks, Snowflake is a plus
  • Relevant Microsoft Certification (Fabric Analytics Engineer Associate, Azure Data Scientist Associate) is a plus.
  • Outstanding communication skills, with demonstrated ability to manage and influence stakeholders at all levels.

What’s in it For You?

  • A company built on Canadian roots and heritage
  • Your work is recognized with a comprehensive and competitive Total Rewards Program
  • Opportunities for career growth through numerous internal and external programs
  • Recognize and be recognized by your peers with our Goose Rewards & ICON Rewards
  • Be a part of CG Gives. Donation matching and paid volunteer time to help the organizations you care about
  • Access to tools and resources to support physical and mental health, embracing change and connecting with colleagues
  • Inspiring leaders and colleagues who will lift you up and help you grow

We believe in the power of inclusion and are passionate about building and sustaining an inclusive and equitable working environment where all employees can bring their authentic selves to work everyday.  We believe every one of our team members enriches our diversity by exposing us to varying ways to understand the world, identify challenges, and to discover, design, produce, and deliver great products and service. Our different perspectives are what enable us to create, dream and live in the open.

Canada Goose is an equal opportunity employer and is committed to providing employment accommodation in accordance with the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act.

There are multiple ways to interview with us! If you require any interview accommodation for your interview, please e-mail us at [email protected].

Top Skills

Azure Data & Analytics
Databricks
Microsoft Fabric
Power BI
Pyspark
Python
R
Snowflake
SQL
Tableau

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