Senior Data Scientist, GTM Data Science

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, 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. .
The Role
The Sales and Account Management (SAM) Data Science team leverages experimentation, advanced measurement frameworks, machine learning, and statistical techniques to improve the incremental revenue generated by the SAM organization.
As a Senior Data Scientist you will partner closely with Machine Learning, Data Engineering, Analytics, Business Strategy, and Leadership to develop and monitor predictive models, design and analyze experiments, develop statistical frameworks, and embed data-driven operations across the organization. You will apply advanced statistical methods to answer complex business problems and guide decision making across Square's go-to-market business units.
You Will

• Deeply understand the Sales and Account Management data ecosystem, and apply data science techniques to support the growth of the organization
• Be the subject matter expert for our revenue forecasting models and how they are applied to the Sales organization. While you will not be developing the model, you will be responsible for understanding how it works, explaining it to non-technical stakeholders, and answering questions around performance and explainability.
• Partner with Machine Learning engineers to support measurement and evaluation of ML models
• Apply descriptive and predictive analytics to help drive insights and business decisions
• Communicate analyses and decisions to high-level stakeholders and executives in verbal, visual, and written formats
• Apply a diverse set of tactics such as causal inference, quantitative reasoning, and machine learning to research and produce insights
• Mentor and coach other data scientists and analysts on the team by providing technical guidance

You Have

• 8+ years of experience in quantitative analytics, data science, or analytical consulting, or 6+ years of experience with an M.S in a quantitative field (computer science, statistics, economics, or similar STEM field)
• Familiarity with the domains of marketing attribution, lifetime value modeling, and ROI measurements
• Expertise in statistical analysis, hypothesis testing, and experimental design
• Strong project management skills, with the ability to manage multiple projects and priorities in a fast-paced environment.
• Strong written and verbal communication skills and ability to build relationships and influence across the organization
• Proven ability to facilitate cross-functional projects that depend on the contributions of others in a variety of disciplines
• Fluency with data warehouse design practices, analytics, and visualization technologies (we use SQL, Looker, and Python)
• Expertise with concepts beyond querying (schema and ETL design, and query optimization)

Nice to have

• Experience applying both statistical and machine-learning techniques to solve practical product problems such as forecasting revenue, predicting churn, estimating LTV, and improving connect rate
• Experience working with revenue-generating teams such as Sales, Account Management, or Marketing

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 an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We also consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.
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 .
Block will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.
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.
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.
Zone A:
$171,800 - $257,600 USD
Zone B:
$163,200 - $244,800 USD
Zone C:
$154,600 - $232,000 USD
Zone D:
$146,000 - $219,000 USD
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.