The Data Scientist will query and analyze large, complex datasets to generate insights that support revenue cycle optimization across an evolving cancer care delivery environment. This role applies advanced analytics, statistical modeling, and machine learning techniques to improve financial performance, streamline end-to-end revenue cycle operations, and enhance the patient financial experience. Working closely with revenue cycle leadership, clinical teams, and IT partners, this role translates data into actionable strategies that improve reimbursement, reduce denials, and optimize operational efficiency. As a successful candidate, you will: • 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 Your qualifications should include: • 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), along with data visualization tools such as Tableau • 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 City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location.