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# Data Analyst

- **Company:** LMI
- **Location:** Tysons, VA, United States
- **Experience:** Experienced
- **Salary:** $120,000.0 - $145,000.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Health Informatics, Information Systems, Data Cleansing, Data Dictionary, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Profiling, Data Warehousing, Database Queries, Decision Support Systems, R (Programming Language), Intelligence Analysis, Python (Programming Language), Microsoft SQL Server, Power BI, SAS (Software), SQL Databases, Tableau (Software), Azure Data Factory, Snowflake, Powerquery, Microsoft Fabric, Information Technology, Data Analytics, Data Management, Software Version Control, Databricks
- **Published:** October 2, 2026
- **Apply:** https://careers-lmi.icims.com/jobs/14666/data-analyst/job?mode=apply&apply=yes&in_iframe=1&hashed=-336058770

## About the Role

Candidates should independently execute well-scoped analyses and manage recurring analytical products. Level IV candidates should bring deeper experience owning complex multi-source analysis, shaping approaches, reviewing work, and advising stakeholders. Strong candidates combine practical SQL and analytical skills with disciplined documentation, data-quality judgment, and concise communication., * Bachelor's degree in data analytics, statistics, mathematics, economics, operations research, computer science, information systems, public health, engineering, or a related quantitative field; equivalent experience may be considered.

 * 4+ years of relevant data analysis, business intelligence, performance analysis, reporting, or operational analytics experience. Level IV placement will generally require 7+ years plus independent ownership of complex analysis.
 * Strong SQL skills and proficiency with at least one additional analytical tool such as Python, R, SAS, advanced Excel, Power Query, or a comparable platform.
 * Experience preparing and validating multi-source data, including joins, transformations, duplicate handling, missing-data review, exception analysis, and reconciliation.
 * Working knowledge of descriptive statistics, trends, distributions, baselines, comparisons, sampling concepts, and appropriate interpretation of observational data.
 * Experience developing analytical tables, dashboards, visualizations, reports, or decision-support products with traceable source data and calculation logic.
 * Ability to translate ambiguous stakeholder questions into clear analytical requirements and adjust the approach when available data does not support the original request.
 * Strong data-quality judgment and clear communication of definitions, assumptions, methods, limitations, and uncertainty to technical and non-technical audiences.
 * Experience maintaining reproducible analytical work through documented queries/code, data dictionaries, version control, peer review, or comparable quality practices.
 * Recommended certification: Microsoft Power BI Data Analyst, Azure Data Fundamentals, Tableau Certified Data Analyst, or a comparable analytics credential.
 * Ability to satisfy VA personnel vetting and applicable security, privacy, records-management, and data-handling requirements., * 6+ years supporting enterprise, federal, healthcare, operational, program, or mission analytics; 8+ years is especially valuable for Level IV candidates.
 * Prior VA, VHA, federal health, or other federal analytics experience in a large, governed enterprise environment.
 * Experience with healthcare, workforce, utilization, productivity, workflow, adoption, service delivery, quality, customer experience, or outcome data.
 * Advanced experience with Power BI, DAX, Power Query, SQL Server, Microsoft Fabric, Databricks, Snowflake, Tableau, or comparable enterprise analytics technologies.
 * Experience with APIs, semantic models, data warehouses/lakehouses, ETL/ELT outputs, or governed datasets and coordination with data engineering teams.
 * Experience supporting pilot analysis, implementation measurement, program evaluation, benefits tracking, or AI/ML evaluation under appropriate technical leadership.
 * Additional certification or training in Power BI, Fabric, Databricks, Tableau, cloud analytics, SQL/data engineering, statistics, or Lean Six Sigma is preferred.

## Description

LMI is seeking a Data Analyst to support Department of Veterans Affairs (VA) modernization initiatives. These full-time positions provide scalable, hands-on analytical capacity across operational improvement, digital modernization, workflow analysis, performance measurement, data-quality assessment, reporting, and decision support.

This position follows a hybrid work model, with an expectation of approximately 25% onsite presence at LMI's Tysons headquarters or Washington, DC.

The analysts will turn business and mission questions into defensible analysis by identifying data needs, assessing source quality, preparing and validating data, performing exploratory and recurring analysis, and presenting results in clear, decision-ready formats. Work may include ad-hoc analysis, dashboards, baselines, trends, cohorts, data profiling, and support to pilots or implementation decisions.

The role works closely with data science, data integration, program evaluation, clinical informatics, delivery, and technical teams. Specialized leads retain responsibility for advanced modeling, formal evaluation methodology, complex integration architecture, and clinical interpretation; these analysts provide the scalable execution needed to move multiple workstreams forward., * Profile enterprise, operational, workflow, program, survey, or other approved data for availability, completeness, consistency, quality, and fitness for use.

 * Extract, query, join, clean, transform, and validate data using SQL and tools such as Python, R, Excel, Power Query, or comparable platforms.
 * Perform exploratory, descriptive, trend, cohort, segmentation, variance, and before/after analysis appropriate to the decision need and available data.
 * Build analysis-ready datasets, analytical tables, visualizations, dashboards, and concise decision-support products for technical and non-technical audiences.
 * Translate stakeholder questions into data requirements, metric definitions, filters, denominators, business rules, validation checks, and analytical outputs.
 * Document sources, definitions, transformations, assumptions, exclusions, calculation logic, validation steps, and known limitations so results are reproducible and reviewable.
 * Reconcile discrepancies across systems, reports, dashboards, or stakeholder calculations and identify the source of inconsistent results.
 * Support data-readiness assessments by identifying authoritative sources, access dependencies, missing fields, sensitivity constraints, and material data-quality risks.
 * Partner with data integration and engineering resources when analysis depends on new extracts, mappings, pipelines, interfaces, or automated data movement.
 * Support data science and evaluation work through data preparation, descriptive baselines, validation datasets, quality checks, and interpretation of source limitations.
 * Automate repeatable preparation, validation, calculation, and reporting steps where practical and maintain organized code, files, dictionaries, and version history.
 * Perform quality assurance and reasonableness checks before results are released; escalate data or methodology concerns that could materially change conclusions.
 * Communicate findings in plain language, including what changed, what appears meaningful, what remains uncertain, and what the data cannot support.
 * Lead higher-complexity analysis, conduct peer review, mentor analysts, and represent the analytical team in stakeholder discussions.


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