Data Analyst

Zearn•New York, NY

16d•$75,000 - $85,000•Remote

About The Position

The purpose of Zearn Zearn is the nonprofit educational organization whose mission is to inspire all kids to love learning math. Everything we do is driven by our belief that every kid is a math kid. Our top-rated learning platform is designed to catch kids up and move them forward in grade-level math. And it works. Large-scale efficacy research shows students who use Zearn make significant gains in math proficiency, including the students who start multiple grade levels behind. As a nonprofit, all of our work is driven by what is best for kids. At the same time, we operate as an intense and fast-moving technology company, inclusively solving hard problems that will impact current and future generations. The problems we solve require expertise in teaching, learning science, software development, design, video production, and countless other disciplines. As an organization that is always stretching to get to the next level of impact, every single person owns mission critical work. If you’re ready to join our Team of problem solvers, and own work that will drive us to achieve impact at scale, we are looking for you. Learn more about us at https://about.zearn.org/. The Data Analyst at Zearn will create analyses and reports that empower teams across the organization to make better, faster, and more informed decisions to advance Zearn’s mission: helping all children learn and love math. You’ll work as part of the team to optimize and maintain the data models that power your analyses and visualizations. You’ll operate at the intersection of data infrastructure, analytics, and storytelling, ensuring that Zearn’s data is accurate, accessible, and actionable. In partnership with other teams across Zearn, you’ll measure impact, communicate with partners and funders, and scale success. This is achieved by: Driving insight generation and cross-functional enablement, transforming raw data into clear, actionable insights that drive decisions across Zearn. Partner with stakeholders across Zearn, with varying levels of data fluency, to define questions, conduct analyses, and communicate findings that guide strategy and execution. Translate complex data into clear narratives and recommendations, elevating the role of data in planning, prioritization, and measurement. Build analytical models and dashboards that track key performance metrics, ensuring leaders have the visibility they need to evaluate impact and inform next steps. Develop repeatable, high-impact analyses that reduce one-off data requests and increase analytical self-service across the organization. Developing and maintaining data infrastructure, ensuring Zearn’s analytics foundation is reliable, scalable, and usable. Partner with Software, Data Engineers, and Senior Analysts to improve data pipelines, documentation, and schema design. Establish and enforce data governance standards, ensuring quality, consistency, and accuracy across all reporting systems. Identify and address data reliability gaps, proactively improving data health and strengthening trust in analytics outputs. Implement repeatable or automated data quality checks to surface anomalies early and reduce downstream reporting errors. Own the ongoing design, iteration, and maintenance of dashboards and analytical tools, ensuring they remain accurate, usable, and aligned with Zearn’s evolving priorities. Identify recurring questions or points of confusion in reporting and proactively improve metric definitions, visualizations, or documentation to increase clarity and adoption.

Requirements

Growth Mindset: If you don’t know how to do something, try your best to figure it out, whether that means reading documentation, asking colleagues, or developing creative debugging queries. If you cause a disaster, work collaboratively with the team to develop better systems and guardrails to prevent it from recurring.
Technical Mastery: You understand relational data structures, and can use Python or similar languages to automate workflows and analyses.
Strategic Thinking: You understand how insights connect to business goals and help Zearn scale its impact.
Clarity in Communication: You learn about the context of stakeholder requests so that you can translate complex analyses into insights that are salient for your audience. You recognize potential ambiguities and opportunities for misunderstandings in data requests and you communicate with stakeholders to resolve them.
Cross-Functional Collaboration: You build strong partnerships with both technical and non-technical teams.
Bachelor’s degree (Computer Science, Mathematics, Statistics, Data Science, or a related field preferred)
Familiarity with querying relational databases using languages such as SQL or Python
Familiarity with scripting languages such as Python or R for data manipulation
A passion for education and using data to improve learning outcomes for students.

Responsibilities

Driving insight generation and cross-functional enablement, transforming raw data into clear, actionable insights that drive decisions across Zearn.
Partner with stakeholders across Zearn, with varying levels of data fluency, to define questions, conduct analyses, and communicate findings that guide strategy and execution.
Translate complex data into clear narratives and recommendations, elevating the role of data in planning, prioritization, and measurement.
Build analytical models and dashboards that track key performance metrics, ensuring leaders have the visibility they need to evaluate impact and inform next steps.
Develop repeatable, high-impact analyses that reduce one-off data requests and increase analytical self-service across the organization.
Partner with Software, Data Engineers, and Senior Analysts to improve data pipelines, documentation, and schema design.
Establish and enforce data governance standards, ensuring quality, consistency, and accuracy across all reporting systems.
Identify and address data reliability gaps, proactively improving data health and strengthening trust in analytics outputs.
Implement repeatable or automated data quality checks to surface anomalies early and reduce downstream reporting errors.
Own the ongoing design, iteration, and maintenance of dashboards and analytical tools, ensuring they remain accurate, usable, and aligned with Zearn’s evolving priorities.
Identify recurring questions or points of confusion in reporting and proactively improve metric definitions, visualizations, or documentation to increase clarity and adoption.