Data Scientist Lead, Square F&S

Key Skills

Data science techniques, Looker, Machine learning techniques, Python Programming, SQL

Job Description

Company Description

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.

So we expanded into software and started building integrated, omnichannel solutions – to help sellers sell online, manage inventory, offer buy now, pay later functionality through Afterpay, 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 Description

The goal of this team is to empower Square F&S org with data driven decision making, by defining and developing the metrics and KPIs (actual & forecasted) to track Square business against organizational goals. You will lead the data engineers in the team to build the required laying foundations.You are a self-starter and you are comfortable working cross-functionally with other teams across Square and enrich those relationships.

You will:

• Partner with Square F&S org and be responsible for co-defining metrics & KPIs that will be used to track product’s performance by various GTM, product and other teams.
• Lead, coach and mentor a team of data engineers and build data driven culture in the team.
• Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning to research and produce insights
• Coordinate and solve complex projects that extend beyond the traditional boundaries of product domains, analytics, and data science
• Develop resources to empower data access and self-service so your expertise can be leveraged where it is most impactful

Qualifications

You have:

• 8+ 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)

Nice to have: 

• M.S or Ph.D. in a quantitative field (mathematics, statistics, or similar STEM field)
• Experience working with finance/accounting team on designing metrics to track company’s performance

Additional Information

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

Zone A: USD $184,100 - USD $225,000

Zone B: USD $174,900 - USD $213,700

Zone C: USD $165,700 - USD $202,500

Zone D: USD $156,400 - USD $191,200

To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information. 

Full-time employee benefits include the following:

• Healthcare coverage (Medical, Vision and Dental insurance)
• Health Savings Account and Flexible Spending Account