Remote Sr. Data Scientist - Public Healthcare Fraud Detection & Linked Data Analytics

Description:

• The position is for a Senior Data Scientist focused on Public Healthcare Fraud Detection & Linked Data Analytics.
• This role involves leading advanced analytics and AI/ML modeling initiatives to detect and mitigate fraud in public healthcare programs.
• Responsibilities include designing and implementing innovative fraud detection algorithms and integrating large-scale, multi-source datasets.
• The candidate will translate complex data into actionable insights for both technical and policy audiences.
• Collaboration with stakeholders and mentoring project teams is essential, ensuring adherence to secure, compliant, and reproducible analytical practices.
• This is a part-time, remote role that allows for a significant impact on the integrity of federally funded programs while working in a collaborative and professional environment.

Requirements:

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

Benefits:

• The position offers a flexible, remote work arrangement suitable for a part-time schedule, estimated at 40 hours per month.
• There is an opportunity to contribute to public healthcare fraud prevention at a national scale.
• The work environment is collaborative, supportive, and professionally enriching.
• Engagement with cutting-edge AI/ML technologies and analytical methods is a key benefit.
• Career development and mentorship opportunities within a specialized field are provided.