Senior Data Scientist, Square Go

Company Description

Since we first opened our doors in 2009, the world of commerce has evolved immensely – and so has Square. After enabling anyone to take a payment 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, run a busy kitchen, book appointments, engage loyal buyers, and hire and pay staff. And 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 all in one place.

Today, we’re a partner to sellers of all sizes – large, enterprise-scale businesses with complex commerce operations, sellers just starting out, as well as merchants who began selling with Square and have grown larger over time. Whether it’s the food truck that’s establishing a brick & mortar restaurant, the former sole proprietor adding her first employees, or the entrepreneur expanding from one location to ten, as our sellers scale, so do our solutions. We all grow together.

Job Description

Square Go is a new consumer marketplace and booking management app for businesses using Square Appointments. We are looking to put some of the superpowers that we have built for businesses into the hands of their customers, while helping to grow those businesses by bringing in new customers discovering their next barber, nail salon, or other service provider in our marketplace. You will be the team’s first dedicated data scientist that closely partners with 4–5 software and ML engineers, moving fast and experimentally (e.g. think quarterly planning instead of annual planning), and putting on (and swapping) multiple hats.

You will:

• Partner with the Square Go team to make data-driven decisions that have significant impact;
• Define the data vision and execution for general buyer-facing properties at Square;
• Apply a diverse set of techniques including statistical analysis, machine learning (ML), analytics, and data engineering to generate strategic insights;
• Collaborate with ML engineers on interesting ML initiatives ranging from categorization to search/recommendations;
• Communicate analysis and recommendations to high-level business partners in verbal, visual, and written forms;
• Develop resources and collaboration processes to empower data access and self-service so that your expertise can be leveraged where it is most impactful.

Qualifications

You have:

• 4+ years of data science experience or equivalent;
• Fluency with Python and SQL;
• Solid statistical foundations (e.g. A/B testing);
• Familiarity with standard machine learning concepts (e.g. regression/classification, clustering, offline/online model evaluation) and curiosity to learn more modern techniques (e.g. NLP) as required;
• Familiarity with data engineering best practices;
• Experience leading cross-functional projects and partnering with Product/Engineering/Marketing/Design on strategy and prioritization;
• Excellent verbal and written communication.

Nice to have:

• M.S or Ph.D. in a quantitative field (e.g. mathematics, statistics, or similar STEM field);
• Experience working on online marketplace products / mass market consumer-facing apps.

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 $152,100 - USD $185,900
Zone B: USD $144,500 - USD $176,700
Zone C: USD $136,900 - USD $167,300
Zone D: USD $129,300 - USD $158,100

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. 

Benefits include the following:

• Healthcare coverage
• Retirement Plans including company match 
• Employee Stock Purchase Program
• Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance 
• Paid parental and caregiving leave
• Paid time off
• Learning and Development resources
• Paid Life insurance, AD&D. and disability benefits 
• Perks such as WFH reimbursements and free access to caregiving, legal, and discounted resources 

This role is also eligible to participate in Block's equity plan subject to the te