Data Scientist, Revenue Cycle
New
J
JobgetherHealthcare revenue cycle
Nationwide remote position within the United States.Full-TimeMiddle
Salary53.29 - 85.26 USD per hour
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Job Details
- Experience
- A master's degree with at least some relevant experience, including entry-level candidates, or a bachelor's degree with a minimum of three years of relevant professional experience.
- Required Skills
- PythonSQLMachine LearningSnowflakeTableauData analytics
Requirements
- Have a master's degree with at least some relevant experience, including entry-level candidates, or a bachelor's degree with at least three years of relevant professional experience.
- Demonstrate knowledge of data analytics, statistical modeling, predictive analytics, and machine learning.
- Have experience with at least one programming language, such as Python, R, Java, or C/C++.
- Have strong SQL skills and experience with relational databases, including platforms such as Snowflake.
- Have experience developing dashboards, reports, and visualizations using tools such as Tableau.
- Be familiar with machine learning algorithms and frameworks including Random Forest, XGBoost, and LightGBM.
- Be familiar with deep learning techniques including CNNs, RNNs, and LSTMs.
- Have familiarity with healthcare revenue cycle data, including billing, coding, claims processing, payer workflows, and reimbursement.
- Have experience working with EHR systems, particularly Epic, and analyzing data from healthcare operational systems.
- Be able to communicate analytical findings, make actionable recommendations, and collaborate with finance, clinical operations, IT, and executive stakeholders.
- Demonstrate the ability to manage complex analytics initiatives, coordinate stakeholders, and deliver results within established timelines.
- Cloud platform experience such as AWS or Microsoft Azure and familiarity with modern data science workflows and deployment practices are preferred.
Responsibilities
- Query, process, and analyze complex EHR, billing, claims, and financial datasets to identify revenue leakage and performance gaps.
- Develop, validate, and deploy predictive models for denial management, cash collections, reimbursement, and revenue cycle decisions.
- Partner with revenue cycle, finance, and operational leaders on billing, coding, claims management, and collections.
- Design and maintain dashboards, reports, and visualizations for accounts receivable days, denial rates, net revenue, and other metrics.
- Design and implement pilot programs and analytical experiments to evaluate revenue cycle strategies.
- Analyze payer performance, coding accuracy, claim adjudication, reimbursement processes, and denial drivers.
- Translate analytical findings into actionable recommendations for operational leaders, executives, and non-technical stakeholders.
- Lead analytics projects supporting operational transformation and workflow optimization.
- Collaborate with IT, clinical, and data teams to improve data quality and reporting.
- Evaluate model performance and refine analytical methods as healthcare financial challenges evolve.
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