Principal Data Analyst

Lead the design and execution of the most complex analytical projects, including multi-source data integration, longitudinal analysis, geospatial analysis, and statistical modeling in support of client decision-making.

Translate ambiguous, high-stakes business questions into rigorous analytical frameworks, ensuring methodological soundness and interpretive clarity.

Apply advanced statistical techniques including regression modeling, time-series analysis, clustering, hypothesis testing, and causal inference to produce defensible, high-impact findings.

Develop and maintain sophisticated analytical pipelines, dashboards, and reporting systems that deliver ongoing intelligence to clients and internal stakeholders.

Validate and quality-assure analytical outputs produced by junior and senior analysts, ensuring accuracy, reproducibility, and appropriate handling of data limitations.

Synthesize findings from large, complex datasets into executive-level narratives, visualizations, and recommendations that drive client action.

Define and champion RS21's analytical standards, including best practices for data validation, reproducible analysis, visualization design, and documentation.

Evaluate, recommend, and guide adoption of analytical tools, platforms, and technologies that improve team capability and delivery quality.

Establish code and methodology review processes that ensure consistency and excellence across the Data Analytics practice.

Lead the development of reusable analytical frameworks, templates, and accelerators that increase team velocity on common problem types.

Serve as the technical authority on analytical questions that require senior judgment, including data quality trade-offs, methodological choices, and interpretive risk.

Stay at the forefront of developments in data analytics, visualization, and applied statistics, bringing relevant innovations into RS21's practice.

Serve as the senior analytical relationship owner for RS21's most strategically important client accounts, building trust as a long-term advisory partner.

Engage directly with executive and senior client stakeholders to understand their data maturity, analytical needs, and decision-making context.

Lead client-facing workshops, analytical briefings, and data strategy sessions that deepen client engagement and expand the scope of analytical partnership.

Communicate complex analytical findings with clarity and confidence to non-technical audiences, including agency heads, program executives, and policy makers.

Anticipate evolving client analytical needs and proactively propose analytical approaches, capability investments, or scope expansions that deliver additional value.

Mentor and develop analysts at all levels within the Data Analytics practice, serving as a primary technical role model and professional development resource.

Lead communities of practice, peer learning sessions, and internal knowledge-sharing initiatives that elevate the team's collective analytical capability.

Partner with talent and HR leadership to define competency frameworks, career pathways, and hiring criteria for the Data Analytics job family.

Contribute to onboarding programs for new analysts, ensuring they are equipped with RS21's tools, standards, and client engagement expectations from day one.

Identify skill gaps across the analytics team and recommend targeted learning investments, training programs, or hiring strategies to address them.

Serve as the analytical subject matter expert on high-value and strategic proposals, shaping technical approach, staffing rationale, and differentiated win themes.

Contribute to capture strategy, client discovery, and competitive positioning for analytics-focused opportunities across RS21's priority markets.

Advise executive leadership on analytical trends, emerging client needs, and market opportunities that should inform RS21's growth strategy.

Represent RS21's analytical capabilities at industry conferences, client forums, and external venues through presentations, publications, or panel participation.

Build relationships with academic institutions, technology partners, and peer organizations that strengthen RS21's analytical ecosystem and talent pipeline.

Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Public Policy, or a related quantitative field. Advanced degree (Master's or PhD) strongly preferred.

10+ years of progressive experience in data analysis, business intelligence, or applied analytics, including at least 3 years in a senior or lead analyst role.

Expert-level proficiency in SQL and at least one analytical programming language such as Python or R, including experience with libraries for data manipulation, statistical analysis, and visualization.

Deep experience designing and delivering complex analytical projects from problem definition through insight delivery, including work with messy, incomplete, or multi-source datasets.

Advanced proficiency with data visualization and business intelligence platforms such as Tableau, Power BI, Looker, or equivalent.

Strong grounding in applied statistics, including regression, significance testing, sampling methodology, and uncertainty quantification.

Proven track record of engaging and influencing executive-level stakeholders through data-driven analysis and storytelling.

Demonstrated experience mentoring analysts and contributing to team capability development.

Advanced degree in a quantitative discipline such as Statistics, Applied Mathematics, Data Science, Public Health, or related field.

Experience working with federal, state, or local government clients, including familiarity with government data standards, privacy regulations (e.g., HIPAA, FERPA), and reporting requirements.

Background in healthcare analytics, population health, program evaluation, or social services data.

Experience with geospatial analysis tools such as ArcGIS, QGIS, or Python-based spatial libraries.

Familiarity with cloud-based data platforms such as AWS Redshift, Google BigQuery, Snowflake, or Azure Synapse.

Experience with longitudinal data, panel data methods, or quasi-experimental evaluation designs.

Published work, conference presentations, or other recognized contributions to the data analytics field.

Experience contributing to or leading data strategy, analytics roadmap, or data governance initiatives at an organizational level.