Healthcare Claims Senior Data Scientist

Type of Requisition:

Regular

Clearance Level Must Currently Possess:

None

Clearance Level Must Be Able to Obtain:

None

Public Trust/Other Required:

None

Job Family:

Data Science

Job Qualifications:

Skills:

Big Data, Data Analytics, Data Science, Predictive Modeling, Structured Query Language (SQL)

Certifications:

None

Experience:

7 + years of related experience

US Citizenship Required:

No

Job Description:

Our work depends on a Senior Data Scientist joining our team to support Centers for Medicare and Medicaid Services (CMS) anti-fraud activities. As a Senior Data Scientist supporting the Healthcare Fraud Prevention Partnership (HFPP), you will collaborate with a team of Data Scientists, Subject Matter Experts, and Business Intelligence Developers engaged in Fraud, Waste, and Abuse (FWA) analytics, to develop models and algorithms that detect and describe actionable FWA leads for the HFPP.

The Senior Data Science uses tools such as SAS and Python to analyze healthcare claims across Medicare, Medicaid and private payers within a multi-billion record database made up of a large partnership of public and private healthcare payers.

HOW A SENIOR DATA SCIENTIST WILL MAKE AN IMPACT:

• Responsible for development and overseeing the development and execution of FWA models and algorithms in multi-payer environments by designing, creating, reviewing, and maintaining statistical analysis plans, providing data interpretation and generating reports in support of proposed research questions.

• Facilitating the Data Science team’s collaboration with FWA Subject Matter Experts, Business Intelligence Developers, and clients, to develop meaningful analyses for FWA modeling results and providing predictive analytic statistical support.

• Directing the design and maintenance of automated data pipelines, in collaboration with data engineers and Business Intelligence Developers, feeding analytic outputs to a sever environment where HFPP Partners will interact with their analytic outputs.

• Overseeing development standards adherence and quality review on analytic output to ensure consistency with protocol and adequacy to meet methodological objectives, and to ensure compliance with applicable access standards.

• Documenting processes, best practices, and strategies for existing and future FWA models and algorithms on behalf of the Data Science team, optimizing business efficiencies as it relates to process improvement.

• Guiding and instructing a team of 4-6 Data Scientists.

WHAT YOU'LL NEED TO SUCCEED:

• Masters Degree in Statistics or 7+ years of experience in statistical and computer-science related field(s).

• Proven track record delivering outstanding presentations to clients, stakeholders, and HFPP partners.

• Ability to effectively communicate the key insights and value propositions of the TTP analytic outputs.

• Extensive experience using Python software for healthcare Fraud, Waste and Abuse datamining and statistical modeling.

• Expertise using SQL software for healthcare Fraud, Waste and Abuse datamining and statistical modeling.

• Expertise using Tableau software for healthcare Fraud, Waste and Abuse model presentation.

• 5+ years client relation activities, ingesting and synthesizing customer requirements and effectively communicating complex healthcare analytic outcomes to client satisfaction.

• Experience successfully presenting FWA analytic outcomes to clients, stakeholders, and conferences.

• Expertise in medical terminology and all healthcare coding systems (e.g., ICD-10, CPT, HCPCS, DRG and the like).

• Demonstrated experience datamining for healthcare fraud, waste and abuse in large, multi-payer databases with diverse health care benefit structures and claim processing systems, including private plans (commercial insurance) as well as Federal and State public plans (Medicare and Medicaid).

• Experience researching, interpreting and applying payer medical (coverage) policies (e.g., LCDs, NCDs, private carrier medical policies) and common industry claim edits (e.g., NCCI).

• Prior experience managing or leading multi-person data analytics teams with a focus on healthcare data; strong supervisory experience leading project teams and/or mentorship ability guiding new analysts.

• Demonstrated expertise in the complete Microsoft Office Suite inclu