Data Analyst, Data & Digital Products

ABOUT ULI

The Urban Land Institute is a 501(c)(3) nonprofit research and education organization supported by its members. Founded in 1936, the Institute has more than 48,000 members worldwide representing the full spectrum of land use and real estate development disciplines across private enterprise and public service. ULI's mission is to shape the future of the built environment for transformative impact in communities worldwide.

ABOUT THE TEAM

ULI's Data & Digital Products (DDP) team is small, growing, and building something the organization has never had before: in-house predictive analytics and machine learning capability. For years, ULI's data work centered on maintaining reports and dashboards. That is changing, and this role is part of how it changes.

You'll report to the Lead Software Engineer, who brings hands-on machine learning experience from a previous role and is building this team specifically to grow that capability internally. Day to day, you'll work alongside the rest of the DDP team and with stakeholders across the organization who depend on your analysis to do their jobs.

THE ROLE

This is an early-career analytics role for a curious, detail-oriented professional who wants to build a strong foundation in reporting, data quality, stakeholder-facing analysis, and digital-product measurement while developing practical predictive analytics skills over time.

You will work in SQL and Python from day one, supporting ULI’s membership, event, and digital-product data needs. Initially, your work will focus primarily on producing reliable reports and dashboards, responding to ad hoc analysis requests, maintaining data quality, and translating business questions into clear, actionable insights.

As you build familiarity with ULI’s data, systems, and stakeholders, you will also contribute to the team’s growing predictive analytics capability. This includes supporting data preparation, exploratory analysis, model validation, and related work for projects such as forecasting fall-meeting session attendance, membership churn, donor behavior, and event registration.

You will work closely with the Lead Software Engineer, the Data & Digital Products team, and partners across the organization. This role offers direct mentorship and hands-on exposure to the development of ULI’s internal analytics and machine-learning capabilities, including analytics that support ULI’s member-facing app and web products

WHAT YOU WILL DO

Reporting and Analysis

• Build and maintain reports and dashboards, including HTML dashboards, that turn ULI's membership, event, and digital data into insights staff can act on.
• Write and maintain SQL queries against ULI's data ecosystem for data pulls, segmentation, report datasets, and validation checks.
• Respond to ad-hoc data requests from stakeholders across the organization, translating business questions into clear, well-structured analysis.
• Perform data quality checks and audits across core datasets and help document data definitions and business rules.

Predictive Analytics and Machine Learning

• Contribute to the development and evaluation of ULI’s first in-house predictive models, beginning with an attendance-prediction project that helps inform Fall Meeting marketing and outreach.
• Assist with data preparation, exploratory analysis, and model validation for future projects such as membership churn, foundation donor behavior, and event registration prediction.
• Learn modeling practices directly from the Lead Software Engineer as ULI builds its machine learning capability in-house.

Digital Product Analytics

• Support analytics for ULI's member-facing app and web properties, including contributing to components of the app's knowledge finder features.
• Help measure usage and performance using tools such as GA4 and Looker Studio as needed.

Cross-Team Collaboration

• Partner with the Lead Software Engineer on the build-out of ULI's new member app, learning the platform and contributing as you go.
• Explain technical findings, including machine learning concepts, in plain language for non-technical stakeholders.
• Stay current on analytics tooling, including Python libraries such as pandas, and look for ways to automate recurring reporting.

WHAT ARE WE LOOKING FOR

Required

• 0–2 years of experience in data analytics, business analytics, or a related field; internships, co-ops, academic projects, and coursework involving data analysis are all welcome.
• Working knowledge of SQL, including joins, filtering, and aggregations, with eagerness to build stronger skills against a real production database.
• Foundational Python skills and the ability to use, or quickly learn, libraries such as pandas for data analysis.
• Solid Excel skills, including pivot tables and lookup functions.
• Foundational understanding of statistics: distributions, correlation, and hypothesis testing.
• Genuine interest in predictive analytics and machine learning, with motivation to build those skills on the job.
• Strong written and verbal communication skills, with the ability to explain technical and machine learning concepts in plain English to non-technical audiences.
• An eager, energetic, team-oriented approach, and comfort collaborating with a wide range of colleagues and stakeholders.
• Bachelor's degree in data analytics, business analytics, statistics, information systems, or a related field.

Preferred

• Degree or coursework in data science, statistics, or a related STEM field.
• Certifications or coursework in Python, SQL, or R.
• Exposure to R, VS Code, Jupyter Notebooks, or PyCharm.
• Academic or project experience building or evaluating machine learning models.
• Familiarity with GA4, Looker Studio, or CRM/membership data.
• Experience in a nonprofit, association, or membership-based organization.

WHAT SUCCESS LOOKS LIKE

During your first 90 days, you will build a strong understanding of ULI’s mission, data environment, and key business processes while developing productive relationships with the stakeholders you support. You will learn how ULI uses membership, event, and digital-product data to inform decisions, and begin contributing fresh perspectives as you become familiar with the organization’s priorities and systems.

You will quickly take on hands-on analytics work, including reporting, data validation, SQL queries, and analysis that supports staff across the organization. You will also contribute to the foundational work for ULI’s fall-meeting session-attendance prediction project, such as data preparation, exploratory analysis, and model-validation support. The scope and timing of this work will be guided by data readiness and business needs, with the goal of applying the work to an upcoming ULI meeting cycle.

Alongside these responsibilities, you will partner with the Lead Software Engineer and the Data & Digital Products team on the development of ULI’s new member app. As you learn the platform and its data, you will identify opportunities to support product analytics, improve reporting, and contribute to a better member experience.

COMPENSATION AND BENEFITS

The salary range for this position is $65,822 to $71,581. Actual compensation will be based on experience, education, skills, and other job-related factors. ULI offers a comprehensive benefits package including health, dental, and life insurance; generous vacation leave; and a retirement plan with employer match.

WORKING CONDITIONS

The Urban Land Institute (ULI) is committed to shaping the future of the built environment for transformative impact in communities worldwide, and we embrace our core values of integrity, collaboration, inclusion, and excellence in service to our members. In alignment with the Board of Directors' strong commitment to in-person collaboration, our roles require regular on-site presence to foster teamwork, innovation, and organizational effectiveness. ULI's primary workplace remains its offices, where in-person collaboration supports our mission and service to members.

ULI is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion/creed, sex, national origin, disability, genetic information, pregnancy, veteran or active military status, non-citizenship or citizenship status, arrest or conviction record, credit history, caregiver status, sexual orientation, gender identity, marital or partnership status, familial status, unemployment status, or any other status protected by applicable law.