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Execute statistical modeling and machine learning techniques to analyze large-scale healthcare claims and clinical data. Develop causal inference frameworks to assess vendor ROI and treatment efficacy. Utilize machine learning classifiers to identify and stratify high-risk member cohorts.
Implement deep learning models to forecast future financial liability and generate personalized vendor solution recommendations. Support software engineers and AI architects in designing data models for transactional case management and unstructured contract document parsing. Assist in the implementation of AI-driven business intelligence solutions using Tableau to visualize performance trends.
Support the technical definition of product features by conducting A/B testing and writing user stories following standardized experimental protocols. Ensure all analytical tasks align with established data science roadmaps under the supervision of senior leadership. Position is 100% remote.
Travel: Approximately 3x/year (1 week long) to attend All Company meetings in either Winston-Salem, NC or Charlotte, NC.
Education and Experience Requirements Master’s degree in Computer Science, Data Science, Engineering, or related field. Foreign equivalents accepted. Position requires skills with the following which may be gained through experience or education in degree granting programs (including projects, papers, internships, practical training experiences or similar):
Utilizing Google Cloud BigQuery to perform longitudinal patient analysis on large datasets.
Creating Statistical Modeling & Causal Inference frameworks utilizing Python and R using libraries Scikit-Learn and Statsmodels.
Analysis of medical (TPA) and pharmacy (PBM) claims data, including the interpretation and application of ICD, CPT, and NDC codes, reversal logic, and member eligibility parameters.
Implementation of Natural Language Processing machine learning models, including Transformer architectures, for the automated extraction and semantic binning of keywords from unstructured clinical or legal documents.
Training of Deep Learning models for time-series forecasting and Deep Reinforcement Learning (DRL) for solution recommendation, using PyTorch.
Implementing dbt, GitHub Actions, Git, and Docker within Google Cloud BigQuery to modularize logic and maintain data lineage.
Creation of high-fidelity dashboards using Tableau, including Level of Detail expressions and data blending to surface trends and anomalies in multi-dimensional datasets.
Travel Requirements
Approximately 3x/year (1 week long) to attend All Company meetings in either Winston-Salem, NC or Charlotte, NC. Telecommuting/Remote Work is Permitted Position is 100% remote. Please copy and paste your resume in the email body (do not send attachments, we cannot open them) and email it to candidates at placementservicesusa.com with reference #0020-0005 in the subject line. Thank you.
