General Dynamics Information Technology, delivers next-generation IT solutions and services to the Centers for Medicare & Medicaid Services (CMS) and other Federal Health agencies. GDIT is currently seeking a Machine Learning Team Lead to join our portfolio of Fraud, Waste and Abuse programs. In this role you will consult and provide technical input for our mission and IT service professionals associated with our FWA system programs. This role includes both support of our operational programs and business development and capture related activities.
Lead team of data scientists to develop innovative and advanced solutions to complex problems utilizing AI/ML best practices
Assess and consult on emerging AI/ML technologies and guidance related to system, analytic environment, tools, and data requirements
Extract qualitative and quantitative relationships (i.e., patterns, trends) from large amounts of data using SAS, R, Python, Databricks or other statistical or data mining tools
Develop machine learning or advanced analytic algorithms and data visualization of complex data to detect aberrancies and potential vulnerabilities
Gather and organize information for use in supporting decision-making process
Collect, manipulate, analyze, evaluate, and display data using visualization tools
Implement open-ended data merges, data analysis plans, and perform complex data manipulation and reporting tasks
Develop, write, and present detailed technical solutions to solve open-ended business problems to technical and non-technical audiences
Required Skills and Experience -
Bachelor of Science (BS) and 15 years of related experience, or Masters of Science (MS) and 10 years of related experience.
Experience with healthcare programs.
Ability to prioritize effectively
Excellent oral and written communication; including presentation skills
Candidate must be able to obtain Public Trust clearance and must have lived in the United States at least three (3) out of the last five (5) years
Desired Skills and Experience:
Doctor of Philosophy (PhD)
Experience with Medicare and/or Medicaid data
Experience with fraud detection
Experience using data visualization tools such as Tableau or PowerBI
Experience conducting health care related research and analytics
Experience developing and presenting solutions to complex, open-ended problems
Experience proactively identifying and working collaboratively with stakeholders to resolve data anomalies, data quality, and compliance issues in administrative data
Experience matching and merging disparate data sets
ATTRIBUTES FOR SUCCESS:
Ability to work on multiple tasks simultaneously in a high-pressure customer service environment
Proven ability to inspire and train staff to provide technical guidance as well as excellent customer service
Ability to independently design innovative solutions to complex business problems and present solutions for cross-team buy-in
Excellent interpersonal communication and consensus-building skills with demonstrated ability to present material effectively to all levels of staff.
COVID-19 Vaccination Requirement: To protect the health and safety of its employees and to comply with customer requirements, GDIT may require employees in certain positions to be fully vaccinated against COVID-19. Vaccination requirements will depend on the status of the federal contractor mandate and customer site requirements.
We are GDIT. The people supporting some of the most complex government, defense, and intelligence projects across the country. We deliver. Bringing the expertise needed to understand and advance critical missions. We transform. Shifting the ways clients invest in, integrate, and innovate technology solutions. We ensure today is safe and tomorrow is smarter. We are there. On the ground, beside our clients, in the lab, and everywhere in between. Offering the technology transformations, strategy, and mission services needed to get the job done.
GDIT is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status, or any other protected class.