Data Scientist

• Frame ambiguous revenue-cycle problems as tractable modeling problems and own them end to end such as claim and invoice viability scoring, denial and underpayment prediction, revenue/ARR prediction, and work prioritization from hypothesis to a validated, monitored result in production
• Build and validate models with statistical rigor: thoughtful feature design, sound handling of missingness and class imbalance, calibration, honest evaluation against simple baselines, and a clear treatment of uncertainty
• Design, build, and maintain the data pipelines feeding these models integrating with source collections, billing, and EHR systems and internal data stores, and handling data collection, cleansing, field mapping, and payer/plan normalization with a bias toward reliability and data quality
• Establish and own MLOps practice: model monitoring and drift detection (e.g., population stability), calibration and threshold selection, benchmarking against simple baselines, explainability (e.g., SHAP and interpretable coefficients), experiment and version tracking, and model documentation such as model cards
• Partner with subject-matter experts to encode business-rule and heuristic logic alongside statistical models where that produces a more accurate or more defensible result
• Gather and document business requirements for revenue-cycle initiatives, including workflows, decision points, stakeholder objectives, operational constraints, success criteria, data availability, and underlying business assumptions, and maintain traceability as those requirements evolve.

Senior AI Data Scientist

• Devising and applying state-of-the-art machine learning techniques to solve business and scientific problems.
• Evaluate AI/ML readiness and provide data acquisition recommendations to bridge gaps.
• Visualize data to discover and communicate solutions and opportunities.
• Contribute to the design and development of data science-powered applications and internal platforms.
• Work with modern data ecosystems (cloud platforms, distributed data systems, and real-time pipelines).
• Collaborate with external partners to bring groundbreaking results to PPG operations.
• Work with global teams to translate innovative ideas into deployable digital products and services with quantifiable business impact.
• Stay current on emerging technologies in AI/ML, software engineering, and applied data science.

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Senior AI Data Scientist

Data Scientist