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Lead Data Analyst - MCP - REMOTE

Washington, DC · Architecture/Engineering

This opportunity is contingent upon award.

Lead Data Analyst – Modern Claims Processing (MCP) Program

Location: REMOTE
Company: SteerBridge Strategies, LLC

About SteerBridge Strategies: SteerBridge Strategies, LLC is a Service-Disabled Veteran-Owned Small Business (SDVOSB) dedicated to delivering innovative, technology-driven solutions to the federal government. We work to modernize and improve key processes within federal agencies, with a particular focus on enhancing services for veterans. The Modern Claims Processing (MCP) program is aimed at transforming the claims adjudication process for the Veterans Benefits Administration (VBA) using advanced data analytics and automation.

Position Overview: We are seeking a Lead Data Analyst to join our team supporting the MCP program. This role will involve leading data analysis initiatives, including statistical analysis, machine learning, and natural language processing (NLP) to improve the automation of claims adjudication processes. The Lead Data Analyst will also be responsible for designing and implementing data mapping processes related to the adjudication of disability compensation claims.

Key Responsibilities:

  • Lead data analysis projects using Python for statistical analysis, machine learning, natural language processing, and software development, aimed at enhancing the automation of claims processing for veterans.
  • Design and implement data mapping processes related to Disability Benefits Questionnaires (DBQs) and the VA Schedule for Rating Disabilities (VASRD) criteria.
  • Analyze and work with XSD schema representations of disability benefits questionnaires and other regulatory artifacts to ensure data integration and standardization across claims systems.
  • Apply natural language processing (NLP) methods and machine learning algorithms to analyze Veterans Health Administration (VHA) clinical records and associated data.
  • Collaborate with cross-functional teams to implement machine learning and deep learning algorithms that improve claims adjudication efficiency and accuracy.
  • Provide insights from data analysis that inform decision-making, process improvements, and automation efforts across the MCP program.
  • Mentor junior data analysts and work closely with other technical teams to ensure data solutions meet program goals and compliance standards.

Qualifications:

  • 5+ years of experience with Python for statistical analysis, machine learning, natural language processing, and software development.
  • 2+ years of experience designing and implementing data mapping processes, preferably related to healthcare or claims adjudication systems.
  • 1+ year of experience working with Disability Benefits Questionnaires (DBQs)XSD schema representations, and VASRD regulatory criteria associated with the adjudication of disability compensation claims.
  • Master’s degree in mathematics, statistics, computer science, or a related field.
  • 1+ year of experience working with natural language processing (NLP) methods and machine learning/deep learning algorithms in relation to VHA clinical records and data.

Preferred Skills:

  • Familiarity with VA healthcare data systems and claims processing.
  • Experience applying machine learning and NLP techniques to large, unstructured data sets.
  • Strong analytical skills with the ability to interpret and communicate complex data findings to non-technical stakeholders.

Why SteerBridge? At SteerBridge Strategies, LLC, you’ll be part of a mission-driven team that uses cutting-edge data analytics to support federal agencies and improve the quality of services provided to veterans. We offer a collaborative work environment with opportunities for growth, competitive compensation, and a commitment to work-life balance.

Application Process: To apply, please submit your resume and a cover letter highlighting your experience in data analysis, machine learning, and VA-related projects. We are an equal opportunity employer and encourage veterans and individuals from diverse backgrounds to apply.

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