Data Analyst

Position Summary DIR is seeking a detail-oriented and technically skilled Data Analyst to support the preparation and delivery of high-quality data products for our clients. This role supports a range of projects, including federal and state program evaluations, survey design and data collection efforts, performance measurement and reporting systems, and technical assistance initiatives. The Data Analyst will work with complex, multi-source datasets to support data validation, analysis, and reporting activities that inform policy, program management, and research objectives. This role is responsible for supporting the processing, validation, and documentation of data and for collaborating with project teams to ensure data are accurate, well-structured, and usable for downstream analysis and reporting. The ideal candidate has experience with data programming languages (such as SAS, R, Python, or SQL), strong attention to detail, and the ability to clearly communicate data processes and findings to both technical and non-technical audiences. Experience with SAS is highly preferred given its use across DIR projects, but candidates with strong programming fundamentals and the ability to learn new tools quickly are encouraged to apply. The role also requires the ability to effectively leverage AI tools to support data processing, documentation, and quality assurance tasks, using sound judgment and project guidance to validate outputs and ensure accuracy. Experience with data reporting and visualization tools and prior work with government agencies or large nonprofit organizations are preferred. PRIMARY RESPONSIBILITIES Develop and maintain data processing programs (primarily in SAS) to clean, transform, and prepare datasets for analysis under the direction of senior staff Perform quality control checks to validate data accuracy, completeness, and consistency throughout the data lifecycle Merge, organize, and prepare data from multiple sources for analysis and client delivery Assist in creating and maintaining documentation of data files, processes, and code (e.g., codebooks, processing steps, data decisions) Write data narratives that describe file structure, processing procedures, and any anomalies or limitations Support reporting and visualization efforts, including developing data dashboards and preparation of analysis-ready datasets Communicate data issues, assumptions, and findings to project teams, including non-technical staff Assist with instrument and survey data review and processing Use AI tools to support data cleaning, transformation, documentation, and workflow efficiency Apply AI-assisted approaches to support quality assurance while independently reviewing and validating results for accuracy and reliability Other duties as assigned Requirements Bachelor’s degree in a Social science, Computer science, statistics, or related field 3-5 years of relevant work experience Experience using data programming tools to manage and analyze data Knowledge of social science research and evaluation methodology (preferred) Experience with data programming languages (e.g., SAS, R, Python, or SQL) for data management and transformation Experience with SAS is strongly preferred; willingness and ability to learn SAS in a production environment is required Experience working with large and complex datasets, including survey, observational, or administrative data Ability to identify, troubleshoot, and resolve data issues and inconsistencies, with guidance as needed Experience preparing datasets for analysis, reporting, and client delivery, including de-identification of sensitive data Proficiency in Microsoft Excel and other Microsoft Office applications Familiarity with SQL and ability to write or interpret basic queries is preferred Experience with data visualization or reporting tools (e.g., Power BI, Tableau) is preferred Experience using AI tools (e.g., generative AI or code assistants) to support data-related tasks such as coding, documentation, or quality checks, with careful evaluation of outputs to ensure accuracy and appropriate Strong attention to detail and commitment to data quality and accuracy Ability to manage multiple assignments and meet deadlines in a fast-paced environment Ability to work both independently and collaboratively as part of a team Strong problem-solving skills and ability to address challenges with appropriate supervision Clear written and verbal communication skills, including the ability to explain technical concepts to non-technical audiences Ability to effectively work with AI tools as part of day-to-day workflows, including iterating on outputs and applying judgment in their use Key Competencies Strong attention to detail and commitment to data quality and accuracy Ability to manage multiple assignments and meet deadlines in a fast-paced environment Ability to work both independently and collaboratively as part of a team Strong problem-solving skills and ability to address challenges with appropriate supervision Ability to take direction and adhere closely to standard policies and procedures Typical Physical Demands and Working Conditions Requires sitting, standing, and bending and a normal range of hearing and vision.