Square’s mission is economic empowerment and our team supports this by using data to understand and empathize with our customers, thereby allowing us to build a remarkable experience. The Restaurants team within Square is a focused initiative charged with empowering Food & Drink businesses of all kinds to start, run, and grow their businesses through advanced workflows, specialized products, business insights, and inclusion in the greater Square ecosystem. The Restaurants team owns multiple products that Food & Drink businesses use, such as the Point-of-Sale, the Kitchen Display, as well as the overall Square product experience in the Food & Drink space.
As a Data Scientist, you will use data engineering, analytics, statistics and machine learning to empower data-driven decision-making in the full lifecycle of product development and ensure a cohesive customer experience. You will help lead the effort to define metrics to track progress against organizational goals, develop solutions to personalize product experiences, provide insights to our sellers about their business, and drive strategic decisions with data.
You will:
- Partner directly with the Restaurants product team to make data-driven decisions across the organization by applying descriptive and predictive analytics where it will have a material impact.
- Build foundational metrics and KPIs to measure the health of our business.
- Apply data engineering best practices to build a solid foundation of ETLs to power our analytics, data science and machine learning efforts.
- 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.
- Communicate analysis and decisions to high-level partners and executives in verbal, visual, and written media.
- Help lead the data strategy of embedded product engineering, to help make well-informed architecture and design decisions that affect data at Square.
- Develop resources to empower data access and self-service so your expertise can be leveraged where it is most impactful.
Qualifications:
- 8+ years of analytics and data science experience or equivalent.
- Experience building relationships to influence product partners with data.
- Strong background in data warehouse design and data engineering best practices.
- 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.
- Fluency with data, analytics, and visualization technologies (we use SQL, Looker, and Python).
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.
- 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 (including 12 paid holidays).
- Paid sick leave (1 hour per 26 hours worked (max 80 hours per calendar year to the extent legally permissible) for non-exempt employees and covered by our Flexible Time Off policy for exempt employees).
Learning and Development resources.
Paid Life insurance, AD&D, and disability benefits.
These benefits are further detailed in Block's policies. This role is also eligible to participate in Block's equity plan subject to the terms of the applicable plans and policies, and may be eligible for a sign-on bonus. Sales roles may be eligible to participate in a commission plan subject to the terms of the applicable plans and policies. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.
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, veteran status, 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, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
We’ve noticed a rise in recruiting impersonations across the industry, where individuals are sending fake job offer emails. Contact from any of our recruiters or employees will always come from an email address ending with @block.xyz, @squareup.com, @tidal.com, or @afterpay.com, @clearpay.co.uk.
#J-18808-Ljbffr
