We are seeking a detail-oriented and proficient Data Analyst to support the evaluation of mental health care and suicide prevention programs for the Department of Veterans Affairs (VA). The successful candidate will perform data analysis, data cleansing, and methodology integration tasks under the supervision of the Lead Quantitative Social Scientist. This role is critical for ensuring the quality and integrity of data used in evaluations mandated by the Clay Hunt Act and Hannon Act.

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

Key Responsibilities:

Data Analysis and Management:

• Utilize and manage diverse data sets provided by VA’s Office of Mental Health (OMH) and Office of Suicide Prevention (OSP), including Veterans Outcome Assessment (VOA), satisfaction surveys, clinical templates, Northeastern Program Evaluation Center (NEPEC) collected data, and performance measures to answer program evaluation and assessment questions.
• Implement data cleansing and manipulation to ensure data quality and integrity.
• Conduct statistical analyses and generate analytical data sets as per project requirements.
• Run tests to validate the quality, integrity, and statistical validity of data sets.
• Maintain and update databases, ensuring data is stored securely and is easily accessible for analysis.
• Assist in the development and execution of data analysis methodologies under the guidance of the Lead Quantitative Social Scientist.

Evaluation Support:

• Support the independent evaluation of mental health care and suicide prevention programs to measure effectiveness, cost-effectiveness, and patient satisfaction.
• Perform comparative analyses to determine program effectiveness across various veteran cohorts, sub-groups, and service gaps.
• Identify trends, patterns, and correlations within the data to evaluate program performance.
• Assist in the preparation of annual evaluation reports and Congressionally Mandated Reports (CMR).

Reporting and Documentation:

• Document and organize SAS/SQL/R/Python codes used for data analysis and report generation.
• Prepare data-driven reports, visualizations, and presentations to convey analytical findings clearly.
• Use tools like Tableau, Power BI, or custom scripts to visualize data in a way that is easy to understand for stakeholders.

Communication and Collaboration:

• Communicate any data inaccuracies or deficiencies to the Lead Quantitative Social Scientist and assist in proposing solutions.
• Collaborate with VA program leads, stakeholders, and external partners for data acquisition and methodology review.
• Participate in discovery phase activities, including data collection, stakeholder interviews, and transition meetings.

Quality Assurance:

• Ensure that all analytical work complies with rigorous research standards.
• Support the Lead Quantitative Social Scientist in ensuring that deliverables are accurate, comprehensive, and submitted on time.

Minimum Qualifications:

• Bachelor’s degree in Data Science, Statistics, Computer Science, Public Health, or a related field.
• At least 2-3 years of experience in data analysis, data management, data mining, machine learning, and statistical methodologies.
  • Proficiency in statistical analysis software and programming languages such as SAS, SQL, R, and Python. Experience with developing queries for routine data requests and reports.
  • Experience with data visualization tools and techniques such as Tableau, Power BI, or similar for creating reports and dashboards.
  • Strong understanding of data quality assurance and data cleansing processes.
  • Expertise in building and cleaning databases from multiple data sources, combining cost and performance information.
• Demonstrated ability to pay close attention to detail and ensure high levels of data accuracy.
• Excellent problem-solving skills with attention to detail.
• Strong written and verbal communication skills to effectively convey complex data insights to diverse audiences.
  • Ability to work independently as needed.
• Ability to collaborate with the integrated project team to compile, collate, integrate, and transform large sets of data into simplified, meaningful, and actionable trends and visualizations for non-technical stakeholders.
  • Ability to manage multiple tasks and meet deadlines effectively.
• Ability to pass a government background investigation, including financial, criminal, residential, educational, foreign affiliation, prohibited substance abuse, and employment verifications. Please note that only U.S. citizens are eligible for a suitability determination

Preferred Qualifications:

• Master’s degree in Data Science, Statistics, Computer Science, Public Health, or a related field.
• Demonstrated experience evaluating Mental Health and Suicide Prevention programs.
• Understanding of VA evaluation frameworks and regulatory requirements.
• Experience working with federal contracts, especially within the Department of Veterans Affairs.
• Previous experience conducting independent assessments and drafting Congressionally Mandated Reports.

Target salary range: $55,256 - $86,095

Disclaimer: 

The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances. Final compensation will be determined by a variety of factors including but not limited to your skills, experience, education, and/or certifications.