Associate Metrics & Data Analytics

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:

Data Analysis, Data Mining, Python (Programming Language), Statistical Analysis, Structured Query Language (SQL) Development

Certifications:

None

Experience:

2 + years of related experience

US Citizenship Required:

No

Job Description:

The Associate in Metrics and Data Analytics will be responsible for supporting analytical, statistical, and programming efforts to collect, analyze, and interpret large data sets and develop data-driven solutions to the difficult business challenges of healthcare claims Fraud, Waste and Abuse (FWA).  This individual will study development and execution activities that occur in a multi-payer environment. The team member will have advanced statistical and programming skills and the ability to analyze healthcare claims across Medicare, Medicaid and private payers. They will be responsible for creating, reviewing, and maintaining analysis plans, providing data interpretation and generating reports. These duties will be performed in support of FWA studies using healthcare claims data.

HOW AN ASSOCIATE IN METRICS AND DATA ANALYTICS WILL MAKE AN IMPACT:

• Assist with study design and develop plans for data analysis in support of proposed FWA topics or schemes.

• Develop statistical tools and tests executed against FWA modeling results and provide predictive analytic support and measures of success.

• Prepare timelines for project management and performs and interprets basic and complex analyses against diverse data sets.

• Utilizes knowledge of statistical methods, computer programming and medical understanding to propose and perform additional analyses when appropriate.

• Documents analyses, creates summaries, and presents written and verbal results for FWA study reports as well as to the leadership team.

• Provides quality review on statistical analysis and programs plan to ensure consistency with processes and procedures to meet defined objectives.

• Effectively communicate statistical and data-related concepts to non-statisticians (managers, researchers in other fields, etc.).

• Serve as a analytic support for assigned research and FWA studies using healthcare claims data and other healthcare data sources.

• Collaborate with other statisticians and programmers to identify potential data problems from analytic queries and to take appropriate action to guide the resolution process.

• Exceptional problem-solving abilities, accuracy with work, strong organizational skills, attention to detail and the ability to multi-task while meeting deadlines.

• Excellent communication skills, both written and verbal, and especially the ability to communicate data clearly to clients.

• Ability to work in a fast-paced and agile, team-oriented environment with minimal supervision.

WHAT YOU'LL NEED TO SUCCEED:

• Bachelors or Master’s Degree in Statistics or related field, or an equivalent combination of education of education and experience.

• Superior skills conducting statistical and mathematical modeling and analysis using Python, SQL, Snow SQL, Tableau Server, MS Excel, and Amazon Web Services.

• Experience in other programming languages commonly used in data science will also be considered.

• Advanced skills for modeling and data manipulation purposes.

• Competence and demonstrated expertise in the complete Microsoft Office Suite including: Word, Excel, and PowerPoint.

• Experience working with healthcare administrative data across Medicare, Medicaid, and/or commercial insurance, as well as third party data assets.

DESIRED SKILLS AND ABILITIES:

• Experience with client relation activities, ingesting and synthesizing customer requirements and effectively communicating complex healthcare analytic outcomes to client satisfaction.

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

• 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