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 Dashboard Analytics team plays an essential role in optimizing growth and engagement across the Square ecosystem, by conducting experiments on digital surfaces, distilling data into insights, and influencing decisions with actionable recommendations.
Senior Data Scientist in the role will be working with the teams responsible for sellers' onboarding, Dashboard engagement, or Getting support. As a Data Scientist, you will use data engineering, business intelligence, 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 lead efforts to define metrics that track progress against organizational goals, provide insights to our sellers about their business, and collaborate with a wide range of cross-functional partners to ensure we can drive strategic decisions for our sellers with data.
You will:
- Partner directly with the Dashboard team to make data-driven decisions by applying descriptive and predictive analytics where it will have a material impact
- Build foundational metrics and KPIs in business intelligence tools (e.g. Looker, Amplitude) to measure the health of our business
- Work with the engineering team to implement high quality product event logs
- Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning to research and produce insights
- Prioritize rigorously amidst different stakeholders, ensuring your contributions have the most impact on Square’s strategic decisions & bottom line
- Communicate analysis and decisions to high-level partners and executives in verbal, visual, and written media
- Develop resources to empower data access and self-service so your expertise can be leveraged where it is most impactful
Qualifications
- 5+ years of analytics and data science experience or equivalent
- Experience building relationships to influence product partners with data
- Experience leading and participating in cross-functional projects that depend on the contributions of multiple disciplines
- Experience applying both statistical and machine-learning techniques to solve practical product problems such as predicting churn and defining frameworks to measure success
- Fluency with SQL and Python, and experience with 1+ visualization technologies (we use Looker and Amplitude)
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