Data Management Lead

We are looking for a skilled and adaptable Data Management Lead to assume a client-facing role, supporting our $4.3 billion DOD Healthcare Management System Modernization (DHMSM) program providing the modernization of Electronic Health Record (EHR) capabilities for the Department of Defense. 

WHAT YOU WILL BE DOING

The Data Management Lead will guide a team of Data Scientists and Architects responsible for continually assessing and improving the data quality of the EHR system.  The candidate best suited for this position has experience working in Agile environments and is comfortable guiding a small team of professionals to identify, investigate and resolve issues related to data consistency to ensure the information can effectively support the agency’s decision-making needs.  

Major duties and responsibilities include:

• Develop presentations for leadership to share findings and assist in making actionable recommendations.

• Present on projects within team or beyond to boost understanding, visibility, and business impact

• Perform and support data management tasks that deliver a complete view of Military Health System (MHS) health care data throughout the enterprise to the analytic community and MHS leadership.

• Lead data science projects. Take ownership of whole lifecycle of projects. Communicate with project managers, data science and engineering teams to align progress and collaborate on system integrations.

• Help establish the team’s technical stack (centered on Python, Cloud, ML/DL, Kubernetes); understand COTS product configurations, data and pipeline systems

• Create a fluid, end-to-end vision for how data will flow through DHMSM

• Build a unified data infrastructure and deploy atomic patterns, which address the mechanisms for accessing, processing, transforming and consuming data, giving users a way to address data requirements and scope

• Identify and evaluate current data management technologies

• Research new opportunities for data acquisition

• Maintain a corporate repository of all data management related artifacts and procedures

• Implement measures to ensure data accuracy and accessibility

• Develop solutions to data analytics problem and issues that require depth of technical knowledge and understanding of impact on the end product.

• Ensure data integrity is maintained by completing routine data quality analysis.

FACTORS FOR SUCCESS

• BS degree and 12 – 15 years of prior relevant experience or Masters with 10 – 13 years of prior relevant experience. May possess a Doctorate in technical domain.

• US Citizen, with the ability to obtain an ADP IT-II Public Trust based on the minimum of a Tier 3 investigation. Per contract requirements. 

• Strong content knowledge in Data Modeling, Data Management, Data Marts, and Data Warehouses

• Knowledge of querying and automated processes to extract, model, integrate, and evaluate complex datasets and business problems for practical application.

• Ability to thrive in a fast paced cross-functional environment.

• Knowledge of Data Science principles and toolsets (e.g. Python or R) and related development environments

• Proficient in Microsoft Office products, especially Excel, Word, and PowerPoint.

HOW TO STAND OUT FROM THE CROWD

• Medical Data systems experience and understanding (Cerner, EPIC or other comparable products)

• Experience working with DoD or Federal medical data (DMIX would be a plus)

• Experience with Population Health Tools

• Experience with applying principles found in the Data Management Body of Knowledge (DMBOK)

Original Posting Date:

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.