Data Science Manager -Americas-Remote

Recruiter
Shopify
Location
United States
Posted
09 Apr 2021
Closes
04 May 2021
Ref
0d4d4c02
Function
Technology
Level
Manager
Data Science & Engineering is a crucial part of Shopify's mission to make commerce better for everyone. We organize and interpret petabytes of data to provide solutions for our merchants and stakeholders across the organization. From pipelines and schema design to machine learning products and decision support, data science at Shopify is a diverse role with many opportunities to positively impact our success. The Data Science & Engineering team acts as the impact multiplier for Shopify's product teams, putting over 11 petabytes of data to work to make our merchants more successful. From delivering merchandising insights, to optimizing shipping and processing rates, to reducing credit card fraud, to ad campaign recommendations - our Data Scientists deliver solutions from pipeline to platform via an array of open source tools.

We are looking for Data Science Managers to join our Data Science teamsand help shape the insights and algorithms that will inform ourstrategies as we grow globally.

What your role will look like:
  • Partner closely with product, engineering and other RnD stakeholders to guide their decisions using data
  • Proactively identify and champion projects that solve complex problems across multiple domains
  • Apply specialized skills and fundamental data science methods (e.g. experimental design, recommender systems and machine learning when needed) to inform improvements to our business
  • Design and implement end-to-end data pipelines: work closely with stakeholders to build models, tables or schemas that support business processes
  • Empower teams to build and maintain actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products


Qualifications

You will need to have:
  • 7-10 years of commercial experience as in a data science rolesolving high impact business problems, including 3+ years leading and maintaininghigh performance data science teams
  • Experience building and managing high performance data science teams
  • Experience delivering business impact through analysis and data products
  • Experience building data pipelines and driving ETL design decisions
  • Technical leadership and management experience (you enjoy doing both). You can jump into the code to the level that your direct reports admire and respect, but are also interested in developing people and capacity for your team
  • Experience creating data product strategies, shipping data products, iterating after launch, and trying again
  • Extensive experience using Python including a strong grasp of object oriented programming (OOP) fundamentals
  • Strong ability to prioritize and communicate to technical and non-technical audiences alike

It would be great if you have:
  • Previous experience using Spark (either via Scala or Pyspark)
  • Experience with statistical methods like regression, GLMs or experiment design and analysis, shipping productionizedmachine learning systems or other advanced techniques are also welcome
  • Experience with data storytelling usingTableau, QlikView, Mode, Matplotlib, D3, or similar data visualization tools


All your information will be kept confidential according to EEO guidelines.

If you're interested in helping us shape the future of commerce at Shopify, click the "Apply Now" button to submit your application. Please submit a resume and cover letter with your application. Make sure to tell us how you think you can make an impact at Shopify, and what drew you to the role.

Closing date: April 30, 2021, 5pm EST

At Shopify, we are committed to building and fostering an environment where our employees feel included, valued, and heard. Our belief is that a strong commitment to diversity and inclusion enables us to truly make commerce better for everyone. We strongly encourage applications from Indigenous people, racialized people, people with disabilities, people from gender and sexually diverse communities and/or people with intersectional identities.

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