Sr. Data Scientist - Public Healthcare Fraud Detection & Linked Data Analytics
Sr. Data Scientist - Public Healthcare Fraud Detection & Linked Data Analytics
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Salary Not Disclosed
1 Vacancy
Job Description
Integrity Management Services Inc. (IntegrityM) is a woman-owned small business specializing in assisting government healthcare organizations prevent and detect fraud and abuse in their programs.
At IntegrityM we offer a culture of opportunity recognition and collaboration. We thrive off of these fundamental elements that make IntegrityM a great place to work. We offer the flexibility our employees need to challenge themselves and focus on advancing their professional development and careers. Large company perks. Small company feel.
Location: Remote
Employment Type: Part-Time PRN(estimated 40 hours per month)
Reports To: Vice President of PI
Overview
The Senior Data Scientist handles advanced analytics AI/ML modeling and large-scale data integration to lead the development of fraud detection models for federally funded public healthcare programs to include statistical research policy and cutting-edge technology to detect quantify and mitigate fraud.
Key Responsibilities
- Lead the design development and implementation of advanced fraud detection and risk-scoring algorithms leveraging AI machine learning and explainable AI techniques with a focus on linked cross-agency datasets.
- Architect and oversee secure data pipelines to integrate clean and standardize heterogeneous datasets including federal state and open-source data.
- Apply deterministic and probabilistic record linkage methods within a secure environment ensuring compliance with security protections and statistical purposes requirements.
- Conduct literature reviews to identify and adapt fraud taxonomies definitions measures and behavioral indicators for healthcare fraud.
- Collaborate closely with stakeholders and other agencies to incorporate subject matter expertise into model design.
- Develop analytical workflows for unstructured data preparation data quality assessment and anomaly detection across multi-source linked data.
- Deliver reproducible open-source analytical outputs including datasets codebooks algorithms dashboards and documentation suitable for public release.
- Translate analytical findings into actionable insights for both technical and policy audiences via reports dashboards and briefings.
- Provide technical leadership and mentorship to multidisciplinary project teams ensuring adherence to agile collaborative and transparent project practices.
Requirements
Required Qualifications
- 10 years of progressively responsible experience in data science statistical modeling and advanced analytics with a proven record of operationalizing AI/ML solutions.
- Demonstrated expertise in fraud detection anomaly detection or risk scoring in healthcare finance or other regulated sectors.
- Significant experience integrating and linking large-scale multi-source datasets including restricted and unstructured data.
- Mastery of Python R and similar with experience in distributed processing frameworks (e.g. Spark) and secure cloud environments.
- Strong understanding of statistical methods supervised/unsupervised learning and explainable AI techniques.
- Familiarity with federal data privacy confidentiality laws and secure data handling (HIPAA).
- Exceptional written and verbal communication skills with the ability to produce clear concise and actionable deliverables for diverse stakeholders.
- Degree (Masters or PhD) in Data Science Statistics Computer Science Applied Mathematics or related discipline.
Preferred Qualifications
- Advanced degree (Masters or PhD) in Data Science Statistics Computer Science Applied Mathematics or related discipline.
- Experience working with Medicare Medicaid or other large-scale healthcare claims and provider datasets.
- Knowledge of MOU development for data sharing especially in interagency environments.
- Prior experience with similar secure statistical research environments.
- Track record of publishing or presenting in professional or policy forums.
Required Experience:
Senior IC
Employment Type
Full Time
