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Canadian Tire Corporation, Limited
Senior Data ScientistCanadian Tire Corporation, Limited • Toronto, ON
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Senior Data Scientist

Senior Data Scientist

Canadian Tire Corporation, Limited • Toronto, ON
30+ days ago
Job type
  • Full-time
Job description

What you’ll do

The Senior Data Scientist role provides analytical and technical support in the scope of executing targeted campaigns for our customers. The Senior Data Scientist will be the subject matter expert in combining customer-related data sources, collaborating with teams that produce customer insights, deploying data to execution platforms, and measuring lift in campaigns. The dynamic environment requires individuals with a cross functional background, excellent organizational skills, experience working in an agile project environment, advanced analytical ability, strong communication skills to deal effectively with stakeholders and the ability to work effectively in a team as well as independently. Statistics is your strong suit. You have a strong command of machine learning, data science and software engineering. You’re analytical, a problem-solver, detail-oriented and enjoy working in a high-volume work environment. You’re ambitious, balance technical and business acumen to offer strategic counsel to senior leadership and stakeholders. Thriving in a fast-paced environment, you network on all levels and work with an ‘automate first’ mindset to continuously strive towards efficiency.

  • Partner with business stakeholders to ingest and utilize new data sources as they become available, provide ad hoc business reporting and analysis as requested

  • Work hand-to-hand with stakeholders to understand business problems, developing data-driven solutions to overcome these problems ultimately adding tangible business value

  • Provide insights and analytics on customer segments that influence test designs and hypotheses. For example, you may identify that for a target segment X, they over-index on attribute Y which may be important to include in the creative for campaign Z.

  • Measure post-campaign performance of campaigns, identify potential opportunities, and report on statistical significance. For example, using sales data, measure whether the campaign exposed group spent significantly more than the control group and report the relevant p-values.

  • Write queries that efficiently and accurately integrate customer data from a variety of organizational systems.

  • Ensure generated insights meet standards of analytical and statistical rigour, highlighting gaps where necessary.

  • Provide mentorship to team members on data, code, and data science best practices

  • Lead the creation of efficient, cost-effective high-availability pipelines.

  • Provide ad hoc analytics and recommendations for action as needed.

What you bring

  • M.S degree in Statistics, Engineering, Computer Science or a related field

  • 3+ years of relevant work experience

  • Experience with data science disciplines, including hypothesis testing, statistical modeling, machine learning, recommendation systems, artificial intelligence, cognitive science, deep learning, etc.

  • In-depth experience with Python, SQL

  • Experience using advanced tools such as Hadoop, HIVE etc. and working knowledge with relational and non-relational modeling, database applications and integrations, ETL tools, client/server solutions, and modern query languages

  • Experience with cloud (e.g. AWS, Azure and GCP) and industry standard data warehousing technologies (Cloudera, Snowflake, etc.)

  • Experience in working with Big Data technologies (e.g. Hadoop, HIVE, Spark)

  • Project management, team mentorship and leadership qualities

  • Data intelligence and visualization platforms such as Looker, Google Data Studio, Tableau or other similar tools is preferred

  • MLOps experience is preferred

This posting represents an existing vacancy within our organization.


We may use artificial intelligence tools as part of our recruitment process to assist in the initial screening of resumes. All hiring decisions, including candidate evaluation, selection, and disposition, are made by human recruiters.

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Senior Data Scientist • Toronto, ON

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