About the role
Shopify enables entrepreneurs to better design, set up and manage their online stores. At its core, Shopify is a "retail operating system" that not only facilitates online shopping, but also enables cross-selling on social media platforms. With over 820,000 merchants on the Shopify platform — if combined into one "big bucket" — Shopify is the third largest e-commerce retailer in the U.S. Shopify platform delivers features that allow merchants to compete against the biggest retailers and brands on the planet.
The Data Science & Engineering team acts as the impact multiplier for Shopify’s product teams, putting over 11 petabytes of retail 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. But what does “impact” really mean? For us it means solving merchant problems at scale. For example, most small businesses need additional funds at some point to grow their business. By algorithmically -predicting merchants’ growth potential, Shopify has facilitated over $500 million in capital loans to small business owners That’s one of many different product-lines looking for Senior Data Scientists to partner with and help drive value for our merchants.
One incredibly important area of focus in the eCommerce world are Shipping costs. Shipping is usually one of the top marginal costs of running an online store. Working with our Shipping Services team, your work will help to optimize all areas of fulfillment which can have a huge impact on purchase conversion rates. And, with the launch of Shopify Fulfillment Network, there is a whole new range of data products to be built!
Merchants work hard for each sale. Imagine the disappointment and discouragement they feel when they learn that a sale from months ago was made with a stolen credit card, resulting in losing both the money and the goods from this order. The Risk Algorithms team is at the forefront of fighting against credit-card fraud. If you are interested in working with a diverse and dynamic team on developing near-real time fraud detection models based on petabytes of high quality but highly imbalanced data and influencing business decisions for Fraud Protect (https://www.shopify.com/fraud-protect), join them in making sure that well earned money stays with merchants.
Our Platform team helps merchants meet 100% of their individual needs through apps and services. The endless diversity of our merchants means that each of them requires niche features in commerce that don’t necessarily align with Shopify’s core feature. This team directly impacts Shopify by solving diverse, individual merchant problems at scale through apps and services created by our third party partner ecosystem and we want to make sure that we are as data informed as we can in this approach. With tens of thousands of app developers and partners in our ecosystem, this team helps build recommendation systems around which ones are best suited to a merchants needs.
You will need to have:
- Strong background in machine learning including experience implementing models at scale
- Extensive experience using Python (including scikit-learn) or similar languages
- Extensive experience analyzing data using SQL
It’d be great if you had:
- Previous experience using Spark
- Experience with statistical methods like regression, GLMs or experiment design and analysis
- Exposure to Tableau, QlikView, Mode, Matplotlib, or similar data visualization tools
If you’re interested in helping Shopify shape the future of commerce, click the “Apply now” button to submit your application. Please address your cover letter to Surina.
Closing Date: October 30th at 9AM EDT
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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