Data Analyst II

RS21•Albuquerque, GA

5h•$72,000 - $98,000

About The Position

The Data Analyst II is an analytical contributor who independently designs, executes, and delivers data analysis and visualization work across RS21 client engagements. The role takes analytical questions from problem definition through client-ready findings, makes methodological choices within established frameworks, and communicates results to technical and non-technical audiences. The analyst works across RS21's analytical toolchain, produces reporting and dashboards, applies statistical methods, and adapts to client needs. They provide constructive feedback to junior analysts, contribute to analytical documentation, and continue developing expertise for senior-level contribution. The role is embedded in client delivery and owns assigned analytical workstreams. The analyst clarifies requirements, proposes approaches, flags methodological risks, and keeps delivery moving. They are expected to deliver accurate, timely, persuasive work, communicate with client-centricity, and recognize when a question requires further methodology or domain expertise.

Requirements

Bachelor's degree in Statistics, Mathematics, Economics, Data Science, Public Policy, or a related quantitative field.
3 to 5 years of progressive experience in data analysis or business intelligence, including independently delivering analytical projects from problem definition through client presentation.
Proficiency in SQL and at least one analytical language, Python or R, including libraries for data manipulation, statistical analysis, and visualization.
Advanced proficiency with Tableau, Power BI, Looker, or equivalent BI platforms, including independently designing, publishing, and governing production dashboards.
Strong grounding in applied statistics, including regression, hypothesis testing, sampling methodology, and uncertainty quantification.
Ability to communicate analytical findings clearly to non-technical stakeholders through written reports and live presentations.
Experience managing stakeholder relationships and independently delivering analytical work across client engagements.

Nice To Haves

Experience with geospatial analysis tools such as ArcGIS, QGIS, or Python-based spatial libraries.
Background in advanced analytics, program evaluation, or government data environments.
Familiarity with longitudinal data, panel data methods, or quasi-experimental evaluation designs.
Basic understanding of cloud data platforms such as AWS Redshift, Google BigQuery, or Snowflake.
Background in consulting or multi-client delivery environments with high analytical standards and client communication expectations.
Familiarity with AI-augmented analytics tooling and responsible integration of generative AI into analytical workflows.

Responsibilities

Independently design and execute analytical projects across multi-source datasets, including data extraction, transformation, quality assessment, and exploratory analysis.
Write functional Python or R code for analysis, automation, and reporting, using version control, notebook documentation, and reproducibility practices.
Write, optimize, document, and explain complex SQL queries.
Apply statistical techniques such as regression, significance testing, sampling methodology, and descriptive analysis while communicating uncertainty appropriately.
Design and publish production dashboards in Tableau, Power BI, or equivalent, including multiple data sources, visualization and UX principles, data models, and access design.
Create data narratives using storytelling tools and visualization frameworks, adapting presentation to client and stakeholder audiences.
Use AI productivity tools to accelerate research, analysis, and reporting, critically validating AI-assisted outputs and recognizing risks.
Stay current on AI-augmented analytical tools and share relevant learnings with the analytics team.
Manage stakeholder relationships for assigned engagements, facilitate analytical meetings, communicate findings, and align stakeholders on scope and timelines.
Produce client reports, analytical briefings, and status communications tailored to their audiences.
Apply established data governance frameworks in client environments, documenting ownership, lineage, and metadata under an engagement lead's direction.
Anticipate changing client needs and raise concerns about scope, data quality, or methodological limitations before they create delivery risks.
Validate analytical outputs for accuracy, reproducibility, and appropriate treatment of data limitations; document assumptions, caveats, and quality decisions.
Maintain analytical documentation in Confluence or equivalent so teammates can understand the analysis and its meaning.
Contribute reusable analytical templates, code libraries, and accelerators.
Coach junior analysts through hands-on support, code review, documentation, and pairing.
Collaborate with data engineers and data scientists to connect analytical work to appropriate data assets and model outputs.
Partner with project managers to align analytical delivery with client expectations and contractual constraints, and surface scope and timeline risks early.