Note: The job is a remote job and is open to candidates in USA. CoventBridge Integrity Systems provides investigative services, technology, and expertise to help healthcare and government organizations protect critical programs and address fraud, waste, abuse, and operational risk. The Data Scientist develops predictive and statistical models, machine learning algorithms, data pipelines, reports, and visualizations to support fraud, waste, and abuse detection across Medicare and Medicaid programs, while serving as a technical lead and mentoring data analysts.
Responsibilities
- Lead the development of advanced analytical, predictive, and statistical models by defining data requirements, designing algorithms, and validating model performance
- Apply machine learning and modeling techniques to identify potential fraud, waste, and abuse in Medicare and Medicaid claims
- Develop insights, reports, and visualizations that translate complex data into clear, actionable findings
- Design, implement, and automate data pipelines and reporting solutions to support proactive analytics and operational efficiency
- Develop tools and processes to monitor model performance, data quality, and data accuracy
- Support data analysis teams by developing ad hoc techniques, providing technical guidance, and assisting with complex analytic challenges
- Collaborate with internal and external stakeholders to communicate findings and support investigative and operational needs
- Ensure compliance with PIM guidelines and CMS direction related to data analysis and data management
- Prepare and submit required reports within established timeframes
- Maintain documentation and reporting standards to support transparency, reproducibility, and audit readiness
- Identify opportunities for process improvement and advocate for enhancements to analytic workflows and tools
- Perform other duties as assigned in support of program integrity and organizational goals
Skills
- Expert knowledge of healthcare claims data including Medicare, Medicaid, ICD‑10‑CM, provider identifiers, and reimbursement structures
- Knowledge of Medicare and Medicaid claims processing and program integrity principles
- Proficiency in data science programming languages such as Python, R, and SQL, with the ability to write clear, reproducible code
- Knowledge of machine learning techniques including clustering, decision trees, neural networks, and anomaly detection
- Knowledge of advanced statistical and data mining techniques such as regression, distribution analysis, statistical testing, and social network analysis
- Strong critical‑thinking and problem‑solving skills for evaluating complex datasets and identifying meaningful patterns
- Exceptional verbal and written communication skills for presenting technical findings to diverse audiences
- Ability to manage multiple and conflicting priorities across concurrent projects
- Proficiency with Microsoft Word, Excel, and PowerPoint for documentation and presentation
- Bachelor's degree in Mathematics, Statistics, Data Science, Healthcare Administration, Computer Science, Public Health, or a related quantitative field required
- At least 5 years of experience performing data analysis and modeling using SQL, Python, or R
- At least 3 years of experience applying statistical and data mining techniques and developing machine learning algorithms
- At least 3 years of experience analyzing Medicare, Medicaid, or healthcare claims data
- Experience working in cloud environments such as Databricks, Snowflake, Microsoft Azure, or Amazon Web Services
- At this time, CoventBridge is not considering candidates who require visa sponsorship, currently or in the future, including but not limited to H-1B, H-2B, E-3, TN, O-1, F-1 (OPT/CPT, or J-1 Visa Statuses.)
- Preference given to candidates with post‑graduate coursework or an advanced degree
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
Company Overview