Job Description

This position is posted by Jobgether on behalf of Integrity Management Services, Inc. We are currently looking for a Sr. Data Scientist - Public Healthcare Fraud Detection & Linked Data Analytics in United States.

We are seeking a Senior Data Scientist to lead advanced analytics and AI/ML modeling initiatives for detecting and mitigating fraud in public healthcare programs. This role involves designing and implementing innovative fraud detection algorithms, integrating and linking large-scale, multi-source datasets, and translating complex data into actionable insights for both technical and policy audiences. You will collaborate with stakeholders, mentor project teams, and ensure adherence to secure, compliant, and reproducible analytical practices. This part-time, remote role offers the opportunity to impact the integrity of federally funded programs while working in a collaborative, flexible, and professional environment.

Accountabilities:

• Lead the design, development, and deployment of AI/ML fraud detection and risk-scoring models for public healthcare programs.
• Architect secure data pipelines to integrate, clean, and standardize heterogeneous datasets, including federal, state, and open-source data.
• Apply deterministic and probabilistic record linkage techniques within secure environments to ensure data quality and compliance.
• Conduct research on fraud taxonomies, behavioral indicators, and statistical methods to inform model development.
• Collaborate with stakeholders and other agencies to incorporate domain expertise into analytical workflows.
• Develop and maintain reproducible analytical outputs, including code, datasets, dashboards, and documentation.
• Translate complex analytical findings into actionable recommendations for diverse audiences through reports, dashboards, and briefings.
• Provide technical leadership and mentorship to multidisciplinary teams, promoting agile, transparent, and collaborative practices.

Requirements

• 10+ years of experience in data science, statistical modeling, and AI/ML analytics, with a proven track record of operationalizing advanced solutions.
• Expertise in fraud detection, anomaly detection, or risk scoring in healthcare, finance, or other regulated sectors.
• Experience integrating and linking large-scale, multi-source datasets, including restricted and unstructured data.
• Proficiency in Python, R, and distributed processing frameworks (e.g., Spark); experience with secure cloud environments.
• Deep understanding of statistical methods, supervised and unsupervised learning, and explainable AI techniques.
• Familiarity with federal data privacy laws and secure data handling practices (HIPAA).
• Excellent written and verbal communication skills with ability to convey technical insights to varied audiences.
• Master’s or PhD in Data Science, Statistics, Computer Science, Applied Mathematics, or related discipline.

Preferred Qualifications:

• Experience with Medicare, Medicaid, or other large-scale healthcare claims and provider datasets.
• Knowledge of interagency data sharing agreements (MOUs) and secure statistical research environments.
• Track record of publishing or presenting in professional or policy forums.

Benefits

• Flexible, remote work arrangement suitable for part-time schedule (estimated 40 hours/month).
• Opportunity to contribute to public healthcare fraud prevention at a national scale.
• Collaborative, supportive, and professionally enriching work environment.
• Engagement with cutting-edge AI/ML technologies and analytical methods.
• Career development and mentorship opportunities within a specialized field.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
It compares your profile to the job’s core requirements and past success factors to determine your match score.
Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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