Data Scientist, Revenue Cycle

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🕒 June 16

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Logo of City of Hope

City of Hope

10,000+ employees

🧬 Biotechnology

🔬 Science

🤝 Non-profit

💰 $5.4M Grant - City of Hope on 2024-05

Biotechnology • Science • Non-profit

City of Hope is a nonprofit, NCI-designated comprehensive cancer center and research hospital near Los Angeles that provides patient care, conducts translational biomedical research, and offers education and clinical trials across a national network. It focuses on cancer, diabetes, and other life‑threatening diseases, combining clinical services, laboratory science, training and community outreach to develop new treatments and support patients and families.

📋 Description

• Partner with revenue cycle, finance, and operational leaders to drive data-informed decision making across billing, coding, and collections • Analyze large datasets from EHR, billing, claims, and financial systems to identify revenue leakage and optimization opportunities • Develop and deploy predictive models to improve denials management, cash collections, and reimbursement outcomes • Design and implement pilots to test and optimize revenue cycle strategies in real-time environments • Build dashboards and visualizations to monitor KPIs such as AR days, denial rates, and net revenue performance • Translate complex data findings into actionable insights for operational and executive stakeholders • Identify trends and patterns related to payer performance, coding accuracy, and claim adjudication • Lead analytics projects that support revenue cycle transformation and process improvement initiatives • Collaborate cross-functionally with IT and clinical teams to enhance data quality and reporting capabilities

🎯 Requirements

• Master’s degree with 0+ years of experience, or Bachelor’s degree with 3+ years of relevant experience • Experience with data analytics, statistical modeling, and machine learning techniques • Proficiency in at least one programming language such as Python, R, Java, or C/C++ • Strong experience with SQL and working with relational databases (e.g., Snowflake) • Experience with machine learning methods (e.g., Random Forest, XGBoost, LightGBM) and deep learning techniques (e.g., CNN, RNN, LSTM) • Demonstrated ability to extract, analyze, and interpret data to develop predictive models and drive financial outcomes • Experience creating data visualizations and communicating insights to non-technical audiences • Strong problem-solving skills with the ability to manage complex, cross-functional projects • Familiarity with healthcare revenue cycle data, EHR systems (EPIC), claims, billing, and payer workflows required • Experience with cloud platforms such as AWS or Azure and modern data science tools preferred

🏖️ Benefits

• Comprehensive Benefits

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