CoventBridge Group is the leading worldwide full service investigation solutions company providing: Surveillance, SIU and Compliance, Claims Investigation, Counter-Fraud Programs, Desktop Investigations, Social Media, Record Retrieval, Canvasses and Vendor Management programs. With offices in the UK and U.S. the company provides top tier data privacy and security practices, deploys robust case management technology customized to clients’ needs and delivers worldwide coverage via its 1000 employees and affiliates worldwide.

The Data Analyst II will perform in-depth evaluation and analysis of potential fraud cases and requests for information using claims information and other sources of data. Support the development of complex cases that involve high dollar amounts, sensitive issues, or that otherwise meet criteria for referral to law enforcement, recoupment of overpayment, and/or administrative action based on reactive and proactive data analysis.

In assuming this position, you will be a critical contributor to meeting CoventBridge Group's objective: To provide services to our clients that exceed their expectations and contribute to improved healthcare delivery by identifying and eliminating fraud, waste and abuse.

The Data Analyst II position will report to the Data Supervisor and will work in our Grove City, OH office, or if not local, remotely from a home office.

Responsibilities:

• Work with management, investigators, and analysts to provide key statistical research, analytics, and reporting functions for reactive and proactive case development support and to fulfill law enforcement data requests
• Communicate effectively with internal and external customers, including federal law enforcement officers
• Validate data analysis results and analytically identify potential fraud, waste and/or abuse situations in violation of Medicare/Medicaid laws, guidelines, policies, and regulations
• Support management requests for CMS reporting requirements
• Utilize data analysis techniques such as data mining, statistical modeling, predictive modeling, etc. to detect aberrancies in Medicare/Medicaid claims data, and proactively seeks out and develops leads and cases received from a variety of sources including CMS and OIG, fraud alerts, and referrals from government and private sources
• Work with Statisticians and Data Analysts to provide proactive data analysis results with statistically high probabilities of producing case referrals to law enforcement, overpayments, and/or administrative actions
• Prepare, develop, and participate in provider, beneficiary, law enforcement, or staff training as related to Medicare/Medicaid fraud, waste and/or abuse data analysis
• Strong organizational skills and the ability to effectively manage workload within the established timelines
• Maintain chain of custody on all documents and follow all confidentiality and security guidelines
• Comply with and maintain various documentation and other reporting requirements as needed
• Perform other duties as assigned

Requirements:

• High proficiency level with MS Word and Excel
• Proficiency with database programming languages such as SQL, SAS and/or other applications to perform diverse types of data analysis
• Demonstrated experience in handling large data sets and relational databases
• Effective communication skills (verbal and written) to interpret data outcomes
• Strong critical thinking and problem-solving skills
• Knowledge of Medicare and Medicaid rules and regulation is a plus

Educational/Experience Qualifications:

• Bachelor’s Degree in Mathematics, Statistics, Healthcare Administration, Data Science, or related discipline with preference given to MA or MS recipients, and/or relevant work experience as a data analyst
• 2+ years of SQL or SAS development experience as well as demonstrated knowledge of healthcare and claims, or a combination of education and equivalent work experience
• Demonstrated knowledge of various database management systems in order to input, extract or manipulate information
• Demonstrated experience and knowledge of healthcare information (health claims data; specifically, Medicare and Medicaid, ICD-9-CM and ICD-10-CM codes, physician specialty codes, pharmaceutical data, provider identifiers, etc.) is preferred