Data Analyst

LMI is hiring Data Analysts to support Department of Veterans Affairs modernization initiatives. The analysts will profile and prepare data, conduct operational and exploratory analyses, develop reporting and decision-support products, and communicate findings to stakeholders. The role is hybrid, with approximately 25% onsite presence at Tysons or Washington, DC.

Responsibilities

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

Preferred

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

6+ years supporting enterprise, federal, healthcare, operational, program, or mission analytics; 8+ years is especially valuable for Level IV candidates.

Enterprise analytics

Federal analytics

Healthcare analytics

Program analytics

Mission analytics

VA/VHA experience

Federal health experience

Governed enterprise environments

Healthcare data analysis

Workforce analytics

Utilization analytics

Productivity analytics

Workflow analytics

Adoption analytics

Service delivery analytics

Quality analytics

Customer experience analytics

Outcome data analysis

Power BI

DAX

SQL Server

Microsoft Fabric

Databricks

Snowflake

Tableau

Enterprise analytics technologies

API integration

Semantic modeling

Data warehousing

Lakehouse architecture

ETL/ELT

Governed datasets

Pilot analysis

Implementation measurement

Program evaluation

Benefits tracking

AI/ML evaluation

Power BI certification

Fabric training

Databricks training

Tableau training

Cloud analytics

SQL engineering

Data engineering

Statistics

Lean Six Sigma

Cross-functional collaboration

Benefits

Hybrid work model, with an expectation of approximately 25% onsite presence at LMI’s Tysons headquarters or Washington, DC.

Company

Digital solutions, AI, and software for federal agencies

Tysons Corner, Virginia, USA

http://www.lmi.org/

Founded in 1961

1001-5000 employees

Qualifications

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

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

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.

Required skills

SQL, Python, R, SAS, Excel, Power Query, Data Analysis, Data Quality Assessment, Data Preparation and Validation, Descriptive Statistics, Dashboard Development, Data Visualization, Microsoft Power BI, DAX, SQL Server, Microsoft Fabric, Databricks, Snowflake, Tableau, API Integration, Data Warehousing, ETL/ELT, Program Evaluation

Experience

4+ years