Data Scientist Intern

Best Buy - Burnaby, BC (30+ days ago)

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  • This internship is for the summer of 2020*
  • All applicants must be post-secondary school students*
Data Scientist Intern

Do you love turning huge amounts of raw data into clean, thoughtfully-analyzed intel that can be used to guide strategic decisions? Do you have the technical skills to take on complex data stories, plus the foundational experience to guide and support junior data analysts? If yes, we’re looking for someone like you to join our rapidly growing eCommerce team as a Data Scientist Intern .

At Best Buy Canada, we believe empowered people and teams make smarter, faster, and more creative decisions. Our Technology department is a truly Agile environment, where the distance between any one person and senior leadership is microscopic. Here, you’ll work on something big, small, or super cool and before you can blink 100,000 people will see it. You’ll create fast, learn fast, and develop fast. Oh, and sometimes you’ll fail fast too. That’s ok. (Honestly.) It’s all part of the process.

As a Data Scientist Intern on the Digital Intelligence (DI) team, you’ll be integral to our goal of building seamless online user experiences. As an expert in analytics and eCommerce, you’ll deep-dive into multiple data sources, seeking critical insights and answers to important business questions. In this holistic role, you’ll create revenue-driving business strategies based on analytical insights and leverage your relationships with key stakeholders to communicate them out.

What you’ll be doing:
Stitching, transforming, and cleaning various forms of data, including transactional data, customer behaviour data, and text strings (such as customer reviews)
Developing and using advanced machine learning algorithms and statistics to build predictive models, such as sales forecasting and product price optimization, to support decision making in our eCommerce department
Recommending and supporting tools and services for the management of our data and machine learning algorithms
Leading large analytics projects involving multiple junior analysts by leveraging data management techniques, machine learning technology, and advanced visualization tools
Coordinating with corporate BI to establish clear data pipelines with a high level of data hygiene
Creating team- and department-wide efficiencies by automating tasks and analysis using SQL, R, and Python
Championing a data-driven culture by supporting the eCommerce department to raise its overall analytic IQ through formal training, workshops, insights meetings, and presentations to senior leadership

We hope you are…

Passionate about analytics and eCommerce—you stay up-to-date with industry news and trends, always seeking avenues to roll up your sleeves and help elevate the digital customer experience
Deeply curious—you relentlessly pursue opportunities to understand the ‘why’ behind a trend or anomaly in data. You ask the big, tough questions, and quickly investigate to find the answer
A lifelong learner—you hold an engrained desire to keep evolving your craft and pick up new skills
Striving for continuous improvement—you’re an agile problem-solver with an ability to think on your feet; you work efficiently, deliver results quickly, and continually implement your learnings
An effective communicator—you’re a natural leader with a humble and open-minded attitude; your verbal and written communication skills are top-notch, and you can clearly speak about the value of your work

The experience we need…

Currently enrolled at a Canadian post-secondary institution with a focus on computer science, mathematics, statistics, commerce, or business analysis
Strong grasp of CS fundamentals, algorithms, data structures, and design patterns.
Strong background of statistical modelling, data mining, and machine learning.
Demonstrated projects in machine learning

Bonus Points…

Experience working with Cloud platforms such as Azure, AWS, Google Cloud
Experience working in an agile environment
Experience with API development, data modeling, data warehousing preferred