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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.

LMI is seeking a skilled Senior Health Policy Data Analyst at our headquarters office in Tysons VA. Successful Senior Health Policy Data Analyst demonstrate competency in health data analysis, health policy, project execution, critical thinking, and relationship managementwhile upholding the highest standard of ethical behavior.

The successful applicant will become part of an analytical team that supports public health systems management projects with a primary focus on Medicare and Medicare Advantage. He/She will use strong data analysis skills (e.g., SAS/SQL/Python/Excel) to produce reports and insights that inform Medicare and Medicare Advantage policy including related to risk adjustment.

Ultimately, success in this role comes from a combination of a passion for healthcare policy, exceptional attention to detail and accuracy, top-notch data analysis and presentation skills, commitment to cross-functional teamwork, an outstanding client service ethic and a desire to consistently improve in an organization that is dedicated to excellence. Each day may require the candidate to:

Understand complex and organization-specific datasets;
• Perform analyses to answer routine and ad hoc questions about health systems, population health and regulatory compliance and be able to explain the significance of those analyses to non-technical stakeholders;
• Learn and apply relevant federal policy and regulations to data analysis;
• Develop and improve standard operating procedures; and
• Communicate with systems development experts to design tools and applications to automate the fulfillment of repeat requests;
• Demonstrate a strong commitment to excellence.

Minimum Qualifications

• Bachelor's Degree
• 5 years' experience writing automated processes in SAS and/or SQL, Python or similar language. (Applicant may be required to perform demonstration of coding skills).
• 1-3 years' experience in federal consulting.
• 3 years analyzing healthcare plan data including claims and utilization data, MA and Part D plan bids, plan payments, and/or risk scores.
• 3-5 years' experience in data analysis and reporting in client-facing role.
• Strong Microsoft Office (Excel, PPT) skills required. Applicant may be required to perform demonstration of Excel or analytical skills.
• Superior communication and writing skills on technical subjects. Ability to provide narrative context of data analysis to a non-technical audience.
• Ability to absorb large amounts of new technical and policy knowledge without a lot of guidance.
• Demonstrated Strong interest in health policy.
• Experience producing high quality analytical deliverables with both short-term (i.e., 1 hour) and longer-term (i.e., 1+ months) lead times.
• Demonstrated commitment to delivering outstanding products and service that meet or exceed our client's expectations.
• Ability to multi-task between complex projects during seasonal peak periods

Preferred Qualifications

• Master's Degree
• Experience with audits, compliance, or monitoring
• Experience communicating business requirements to system development experts
• 3-5 years of experience analyzing any of the following (claims/encounter data, enrollment, quality and /or provider data) for the Medicare program
• 3-5 years of experience in federal consulting in an analytic role
• Experience migrating large SAS programs to Python