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    Data Scientist - Toronto, ON, Canada - Sportchek

    Sportchek
    Sportchek Toronto, ON, Canada

    2 weeks ago

    Default job background
    Full time
    Description
    Data Scientist, Decision Support page is loaded Data Scientist, Decision Support
    Apply locations Toronto, ON time type Full time posted on Posted 8 Days Ago job requisition id JR132270 What you'll do
    Seeking a results-oriented data science professional who can support retail, loyalty, and customer analytics.

    The primary focus of this position is to develop robust machine learning models, perform customer and program analytics, and develop analytical measurement frameworks.

    The data scientist will perform analytics in support of customer engagement, loyalty program optimization, and marketing program efficiency. Models, analytics, and insights developed will help achieve the strategic goals of our Retail organization.
    Develop a deep understanding of our Retail business, Loyalty and Credit Card Customers, and Marketing programs.

    Support the development of models and other analytics tools to increase customer engagement, marketing program efficiency, and loyalty program effectiveness.

    Scope and structure data science projects while considering business needs and technical constraints.

    Perform advanced quantitative and statistical analysis of retail, customer and loyalty data to identify trends, patterns, and correlations which will be used in making critical business decisions that enhance business performance.

    Support the development of a robust measurement practice using the latest technologies and advancements in machine learning to provide timely insights.

    Establish Machine Learning/Deep Learning models to improve customer engagement and marketing program performance.
    Provide creative solutions, recommendations, and timely advice that align business needs with analytical/modelling concepts.
    Establish necessary data pipelines to deploy AI/ML solutions.
    S or PhD, preferably in Statistics/Math/Economics/Computer Science or a related quantitative discipline.
    ~3+ years experience developing and implementing data science solutions for retail businesses, or loyalty programs.
    ~ Proficiency in using industry standard programming languages, including Python, R, or SAS.
    ~3+ years of experience querying and analyzing large datasets with tools such as SQL, Spark, etc.
    ~ Demonstrated understanding of statistical techniques to programmatically select (and justify) the right approach given specific business problems and data/technology constraints.
    ~ Familiarity with cloud-based data structures including tools to extract, manipulate and transform data within the cloud. Experience with Databricks and Azure Synapse is an asset.
    ~3+ years interpreting, synthesizing, and presenting complex models and analysis to business partners.
    ~ Excellent oral and written communication skills, with the ability to communicate both technical and business concepts, as well as strong presentation skills.
    ~ We have adopted a hybrid work model whereby employees use a combination of working in office and virtually in service of outcomes. With more than 90 Owned Brands, 1,700 retail locations, financial services, exemplary e-commerce capabilities, and exciting market-leading merchandising strategies. We dream big and work as one to innovate with purpose for our customers at every level of our business, investing in new technologies and products, and doubling down on top talent to drive the company forward. We offer competitive salaries and wages to CTC employees, as well as store discounts, supported learning through our Triangle Learning Academy, Canadian Tire Profit Sharing, and retirement and savings programs for eligible employees.

    Join us in helping to make life in Canada better through living and working our Core Values:

    we are innovators and entrepreneurs at our core, outcomes drive us, inclusion is a must, we are stronger together and we take personal responsibility.

    Our Commitment to Diversity, Inclusion and Belonging

    We are committed to fostering an environment where belonging thrives, and diversity, inclusion and equity are infused into everything we do.

    We believe in building an organizational culture where people are consistently treated with dignity while respecting individual religion, nationality, gender, race, age, perceived ability, spoken language, sexual orientation, and identification.

    We are united in our purpose of being here to help make life in Canada better.
    We stand firm in our Core Value that inclusion is a must.

    We welcome and encourage candidates from equity-seeking groups such as people who identify as racialized, Indigenous, 2SLGBTQIA+, women, people with disabilities, and beyond.

    Should you require any accommodation in applying for this role, or throughout the interview process, please make them known when contacted and we will work with you to help meet your needs.

    Data Engineer
    locations Toronto, ON time type Full time posted on Posted 13 Days Ago Manager, Advanced Analytics & Data Science

    locations Toronto, ON time type Full time posted on Posted 15 Days Ago We are one of Canada's most admired and trusted companies.

    With world-class owned brands and exciting market-leading merchandising strategies, we are continually innovating with purpose: to excite and serve Canadian customers from coast-to-coast.

    We are connected to communities, big and small, from coast-to-coast, offering products and services that reflect the diverse nature of every one of them.

    From sports to outdoors, automobiles to homes, we know and understand life in Canada like no other retailer can.

    We are always on the lookout for curious, creative people who are able to navigate and excel in a rapidly evolving retail environment.

    If you're ready to take on new challenges – be it in digital, IT, marketing, data & analytics, merchandising, or one of the many other roles we have – there is a place for you here, so apply today.

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