Company Description
Shopify is the leading omni-channel commerce platform. Merchants use Shopify to design, set up, and manage their stores across multiple sales channels, including mobile, web, social media, marketplaces, brick-and-mortar locations, and pop-up shops. The platform also provides merchants with a powerful back-office and a single view of their business, from payments to shipping. The Shopify platform was engineered for reliability and scale, making enterprise-level technology available to businesses of all sizes. Headquartered in Ottawa, Canada, Shopify currently powers over 2,000,000 businesses in approximately 175 countries and is trusted by brands such as Allbirds, Gymshark, PepsiCo, Staples, and many more.
Shopify has redefined commerce, raising the standard for how businesses of all sizes manage, market and sell their products and services. Powered by the most innovative platform on the market, we continue to grow rapidly while constantly looking for new ways to impact and disrupt markets.
Job Description
About the role
Within Merchant Services, our job is to build superpowers that put small businesses on a level playing field with the largest e-commerce players.
As a Staff Data Scientist, you are expected to play a crucial role pushing forward product development across multiple domains. Staff Data Scientists do this by informing high-level product strategy and execution, building a strong and broad operating picture allowing us to move quickly, and/or improving underlying algorithms, heuristics and rules powering individual products. We expect a very high degree of autonomy and proactivity, as well as the ability to compound the work of multiple data scientists into powerful conclusions.
Responsibilities:
- Proactively identify and champion projects that solve critical problems for merchants
- Partner closely with product, engineering and other business leaders to influence product and program decisions with data
- Own the operating picture and use a strong analytical toolbox to highlight opportunities and guide execution
- Build actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products
- Influence leadership to drive more data-informed decisions
- Define and advance best practices within data science and product teams
Qualifications
Qualifications:
- Experience in end-to-end lifecycle of ML model - conceptualizing, building and deploying ML model in production environment
- Proficiency in Python and experience with software architecture and system design