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Square
Senior Data Scientist, eCommerce
at Square
7 months ago | 682 views | Be the first one to apply

Senior Data Scientist, eCommerce

Full-time
Canada

About the company

Since we opened our doors in 2009, the world of commerce has evolved immensely, and so has Square. After enabling anyone to take payments and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together. To solve this problem, we expanded into software and built integrated solutions to help sellers sell online, manage inventory, book appointments, engage loyal buyers, and hire and pay staff. Across it all, we’ve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow in one place. Afterpay furthers our goal to provide omnichannel tools that unlock meaningful value and growth, enabling sellers to capture the next generation shopper, increase order sizes, and compete at a larger scale. Today, we are a partner to sellers of all sizes – large, enterprise-scale businesses with complex operations, sellers just starting, as well as merchants who began selling with Square and have grown larger over time. As our sellers grow, so do our solutions. There is a massive opportunity in front of us. We’re building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same.

Job Summary

You Will:

📍Partner with product managers, engineers, and senior strategy leaders to improve the product. Make sure the right questions are being asked, solicit feedback, and iterate until you reach meaningful conclusions backed by solid analysis 📍Design and analyze A/B experiments to evaluate the impact of changes we make to the product 📍Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning to research and produce insights 📍Use SQL on a daily basis to develop data pipelines, write complex queries, and perform analysis 📍Communicate analysis and decisions to high-level partners and executives in verbal, visual, and written media 📍Develop resources to empower data access and self-service so your expertise can be leveraged where it is most impactful 📍Develop, debug, and improve data models. Our product moves fast and new data doesn’t always play nice with existing models. Think about how to ingest and store data in the most useful and scalable format. 📍Define KPIs, build ETLs, construct dashboards and other tools for you and other stakeholders

Qualifications

📍4+ years of analytics and data science experience or equivalent 📍Experience building relationships to influence product partners with data 📍Experience leading cross-functional projects that depend on the contributions of others in multiple disciplines 📍Experience applying both statistical and machine-learning techniques to solve practical product problems such as predicting churn, defining frameworks for measuring success, and clustering user archetypes 📍Familiarity with data warehouse design and best practices Fluency with data, analytics, and visualization technologies (we use SQL, Looker, and Python)

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