CITY RESEARCH SCIENTIST

About the Agency: The Department of Housing Preservation and Development (HPD) oversees housing standards across all 3.7 million homes in New York City. As the nation’s largest municipal housing agency, HPD is responsible for building and preserving affordable housing, protecting tenants from harassment and displacement, and holding landlords accountable across the five boroughs. Under Commissioner Dina Levy and the Mamdani Administration, HPD is pursuing an ambitious housing agenda focused on the needs of New York’s tenants. With a broad set of tools including standards enforcement, tenant resources, and the creation of new affordable housing, HPD is committed to making New York City a more affordable place for renters and homeowners alike. Your Team: The Office of Policy and Strategy (OPS) leverage its expertise to guide and support HPD and its many Offices in their efforts to deepen their impact, optimize their efficiency, and become more data-driven, climate-adaptive, and mission-focused. As part of OPS, the Division of Strategic Operations and Analytics (SOA) works to increase HPD's impact by analyzing and improving operations agency-wide. SOA does this by clarifying HPD program missions, objectives, and stakeholders; implementing initiatives that advance HPD's goals; analyzing data to deliver actionable insights to HPD programs; and increasing the agency's overall ability to leverage data. Your Impact: As the Analytics & Reporting Engineer within SOA, you will play a key role in making HPD’s data more accessible, reliable, and reusable to support reporting and analytics. By building well-structured datasets, automations and data flows, you will help SOA and other HPD offices turn data into key reporting and metrics that support key agency programs for New Yorkers. Your Role: Your role will focus on hands-on development of data pipelines, curating datasets and data flows in SQL Server and building reusable scripts and code to support reporting and analytics work for agency programs such as homeless placement services, homebuyer assistance, housing distress & compliance, and fair housing work. You will also create and maintain reports and dashboards, or related dataflows/models. Exercising independent judgement and initiative, you will implement solutions through scalable data models, automated workflows, and well-structured datasets and BI data flows - to enable more efficient reporting, research, and analytics for key agency programs. Your Responsibilities: • Build and maintain core datasets, data models, and dashboards to support key program reporting and analytics • Build and automate Python-based data cleaning and integration pipelines — merging data across siloed source systems and using automation tools — to support reporting needs for housing placements, fair housing and more. • Load cleaned datasets into SQL Server and connect to BI tools (e.g. Power BI) to support reporting/dashboarding. • Implement basic code validation, testing, and documentation practices to keep analytics scripts and datasets reliable and maintainable. • Document code standards and workflows so datasets and scripts remain usable/maintainable by the team over time. • Apply data engineering skills and creative collaboration techniques to address technical issues and drive the approach for the team Preferred skills • Inquisitive, self-motivated problem-solver who is passionate about making organizations more data-driven • Comfortable working in a fast-moving, resource-constrained environment with messy data and legacy systems; motivated by rolling up your sleeves and building practical tools that make a real impact on people's lives. • Experience building or supporting data pipelines (ETL/ELT) — extracting, cleaning, and transforming data from multiple sources. • Experience working with relational databases (e.g., SQL Server or similar) • Some experience with BI data modeling (preferably Power BI or similar) is a plus • Familiarity with source control and version control workflows (e.g., Azure DevOps Repos) • Strong interpersonal and organizational skills; able to ask thoughtful questions and collaborate across teams • Strong aptitude for learning new tools and technologies independently using online resources • Technical skills: SQL, Python, Power BI data modeling (DAX, Power Query M), and data modeling fundamentals