POSITION SUMMARY

As a Data Analyst II, you will conduct thorough evaluations and advanced analyses of potential fraud cases and data inquiries by leveraging claims information and multiple data sources. Provide critical support in developing complex, high-value, or sensitive cases that warrant referral to law enforcement, recovery of overpayments, or administrative action—driven by both proactive and reactive data analysis strategies.
The Data Analyst II position will report to the Data Supervisor and will work in our Grove City, OH office. If not local, remotely from a home office.
Responsibilities/ Requirements:

REQUIRED QUALIFICATIONS

• Bachelor’s or Master’s degree in Mathematics, Statistics, Health Informatics, Data Science, or a related field.
• Minimum 2 years’ experience analyzing Medicare and/or Medicaid data.
• Minimum 2 years’ experience in SQL and Python.
• Working knowledge of SAS, Databricks, Snowflake, or Spark.
• Experience with libraries like Pandas, NumPy, Scikit-learn, or visualization tools like Seaborn, Matplotlib, Tableau, or Power BI.
• Strong understanding of healthcare claims, ICD codes, provider identifiers, and Medicare/Medicaid billing practices.
• Exceptional organizational, communication, and problem-solving skills.

PREFERRED QUALIFICATIONS

• Experience working with any state Medicaid agency, Medicaid Administrative Contractor, or Unified Program Integrity Contractor (UPIC).
• Experience in transitioning from SAS to more modern tools (e.g., Databricks, Snowflake).
• Familiarity with CMS reporting and fraud detection protocols.

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

Benefits:

• Medical, Dental, Vision plans
• Life, LTD and STD paid by the employer
• 401(k) with company match up to 4%
• Paid Time Off and company paid holidays
• Tuition assistance after 1 year of service

The salary range for this role is $60,000 to $75,000 annually. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee’s pay position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

ABOUT US:

CoventBridge Group is the global leader in full-service investigations providing Surveillance, SIU and Compliance, Claims Investigation, Counter-Fraud Programs, Desktop Investigations, Social Media, Record Retrieval, Canvasses and Vendor Management programs. 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.
CoventBridge is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, caste, disability, veteran status, and other legally protected characteristics and maintains a drug-free workplace.
CoventBridge is committed to the full inclusion of all qualified individuals. As part of this commitment, CoventBridge will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact: Human Resources; 888-932-7364; humanresources@coventbridge.com.
https://coventbridge.com/licensing

• Perform comprehensive analysis of healthcare claims data using advanced statistical and analytical methods; prepare clear, concise, and well-structured reports summarizing key findings.
• Collaborate with management, investigators, and analysts to support both proactive and reactive case development efforts by fulfilling data requests.
• Apply techniques such as data mining, statistical modeling, and predictive analytics to identify anomalies in Medicare/Medicaid claims; proactively generate leads and build cases from sources including CMS, OIG, fraud alerts, and various government or private referrals.
• Validate analytical outputs and identify potential fraud, waste, or abuse in alignment with Medicare/Medicaid regulations, policies, and guidelines.
• Communicate analytical insights effectively to internal stakeholders and external partners, including law enforcement agencies.
• Respond to management requests related to CMS reporting requirements with timely and accurate data support.
• Contribute to the development and delivery of training sessions for providers, beneficiaries, staff, and law enforcement on fraud, waste, and abuse detection through data analysis.
• Demonstrate strong organizational skills and manage multiple tasks efficiently while adhering to strict timelines.
• Ensure the integrity and security of all documentation by maintaining proper chain of custody and following confidentiality protocols.
• Adhere to all required documentation standards and reporting procedures as defined by internal and external guidelines.
• Perform other duties as assigned