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. As our sellers scale, so do our solutions. We all grow together.
There is a massive opportunity in front of us. We’re building a business that is big, meaningful, and lasting. And we are helping sellers around the world do the same.

Job Description

The Automation organization is a cross-functional team at Square that accelerates our sellers’ path to value realization by making technology investments that reduce friction and cost and increase personalization across customer interfaces. One of the key pillars of the Automation team is to improve the efficiency and effectiveness of our go-to-market seller-facing teams such as Sales, Account Management, and Customer Success by injecting intelligence into Square’s direct communication paths with sellers. 

As a Data Scientist on the Go-to-Market Automation team, you will use engineering, analytics, and machine learning to drive insights and decision-making for the Sales organization. You will partner closely with strategy and business partners to design experimentation and measure lift of different areas within the program. You will leverage insights from these experiments to inform best practices and drive value within Sales.

You will:

• Design and implement measurement methodologies to rigorously evaluate the business impact of new policies and models on Sales KPIs

• Leverage quasi-experimental techniques to estimate causal parameters using observational data

• Apply descriptive and predictive analytics to help drive insights and business decisions

• Apply a diverse set of tactics such as causal inference, quantitative reasoning, and machine learning to research and produce insights

• Partner closely with cross-functional teams spanning Strategy, Data Engineering, and Sales

• Deeply understand the Sales data ecosystem, and apply data science to support the growth of the organization

• Communicate analysis and decisions to high-level stakeholders and executives in verbal, visual, and written formats

Qualifications

You have:

• 2+ years of analytics and data science experience and a Bachelor’s degree or equivalent

• Experience with designing and executing A/B tests and familiarity with a range of lift and impact methodologies

• Experience applying machine-learning techniques to solve practical product problems such as predicting churn, LTV, cross-selling, connect rate

• Proven ability to facilitate cross-functional projects that depend on the contributions of others in a variety of disciplines

• Strong written and verbal communication skills

• Fluency with data, analytics and visualization technologies (We primarily use SQL, Looker, and Python)

Additional Information

Nice to have: 

• M.S in a quantitative field (computer science, statistics, economics, or similar STEM field)

• Experience using quasi-experimental methods (IV, RDD, DiD, etc…) to estimate causal effects using observational data

• Experience leveraging machine learning techniques in causal inference (DoubleML, Causal Forrest, etc..)

• Experience with state of the industry machine learning packages (CausalML, DoWhy)

• Knowledge of Causal DAGs 

• Experience leveraging Spark (or other distributed computing framework) to build machine learning models

We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. 

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our I+D page. 

Additionally, we consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.

Perks

We want you to be well and thrive. Our global benefits package includes:

• Healthcare coverage
• Retirement Plans
• Employee Stock Purchase Program
• Wellness perks
• Paid parental leave
• Paid time off
• Learning and Development resources

Block, Inc. (NYSE: SQ) is a global technology company with a focus on financial services. Made up of Square, Cash App, Spiral, TIDAL, and TBD, we build tools to help more people access the economy. Square helps sellers run and grow their businesses with its integrated ecosystem of commerce solutions, business software, and banking services. With Cash App, anyone can easily send, spend, or invest their money in stocks or Bitcoin. Spiral (formerly Square Crypto) builds and funds free, open-source Bitcoin projects. Artists use TIDAL to help them succeed as entrepreneurs and connect more deeply with fans. TBD is building an open developer platform to make it easier to access Bitcoin and other blockchain technologies without having to go through an institution.