Waystar
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About This Position Waystar is a market-leading provider of cloud-based healthcare payments software. Our mission-critical platform simplifies the complex revenue cycle for providers, enabling them to get paid faster and more accurately, and focus on patient care. We process billions of transactions annually, leveraging a massive dataset of claims, remittances, and patient data to drive outcomes. With Waystar AltitudeAI™, we are at the forefront of applying AI, generative AI, and advanced automation to transform healthcare finance, reduce administrative burden, and achieve peak financial performance for our clients.
What You’ll Do As the VP of Data Science, you will be a strategic and technical leader reporting directly to the SVP of Data Science + Analytics. Your primary responsibility will be to establish and execute the data science strategy that underpins the evolution of the Waystar AltitudeAI™ platform. This role demands a visionary who can lead a world-class team, driving innovation to solve the most critical challenges in healthcare revenue cycle management (RCM)—from preventing denials and optimizing prior authorizations to delivering transparent patient financial experiences. You must possess deep technical expertise in machine learning, including foundation models, and have consistently delivered production-grade, highly available solutions that yield quantifiable improvements in customer outcomes in complex, regulated environments.
Strategic Leadership & Healthcare Innovation
Develop and champion a comprehensive data science and ML strategy that directly translates into new product capabilities and significant business value for Waystar and its clients, focusing on using data to predict, prevent, and automate RCM workflows.
Establish and steward a portfolio of model types—classification, regression, ranking, forecasting, NLP/LLMs, anomaly detection—that address both clinical and financial objectives.
Integrate heterogeneous model outputs (clinical insights, operational predictions, financial risk scores) into an integrated, governed enterprise data set that supports analytics, product experiences, and downstream decisioning.
Collaborate closely with product, engineering, and commercial leaders to embed data science and ML into core platform offerings, ensuring technical initiatives align with market needs and HIPAA/security compliance.
Spearhead research and deployment of cutting‑edge AI and generative AI solutions—such as using LLMs for policy document interpretation and predictive modeling for claim denial rates—to create differentiated, proprietary technology.
Act as a thought leader with analysts, customers, and prospects; communicate our approach, differentiation, and evidence of impact.
Leading Data Science Teams & MLOps
Attract, mentor, and scale a high‑performing, geographically distributed team of Data Scientists and Machine Learning Engineers, fostering a culture of technical excellence, accountability, and continuous learning.
Define and enforce best practices for the entire machine learning lifecycle in a regulated environment, including robust model governance, versioning, continuous monitoring, and drift detection to ensure accuracy and compliance of all production models.
Ensure the team operates with the highest standards of data governance, privacy (HIPAA), and algorithmic fairness, specifically addressing bias and transparency in models impacting provider finances and patient care.
Technical Expertise in Machine Learning Principles and Healthcare Data
Act as the ultimate technical authority on machine learning principles, statistical rigor, and large‑scale data analysis within the company.
Demonstrated experience and deep theoretical understanding of foundation models (LLMs, VLMs), including model selection, fine‑tuning techniques (LoRA, QLoRA), Retrieval‑Augmented Generation (RAG) implementation, and prompt engineering for generating accurate, context‑aware outputs in a healthcare setting.
Expertise in advanced machine learning algorithms—XGBoost, CNNs, RNNs, Transformer architectures.
Deep familiarity with NLP approaches—concept extraction, human language understanding, summarization—particularly in clinical and healthcare contexts.
Working knowledge of Python, PyTorch, and TensorFlow for developing and scaling machine learning solutions.
Direct the technical architecture and tools used for all data science initiatives, leveraging cloud‑native solutions (AWS, GCP) and distributed computing frameworks to handle Waystar’s massive, multi‑petabyte datasets.
Oversee the design of rigorous A/B testing and experimentation frameworks to accurately measure the clinical and financial impact of deployed ML models on client RCM performance.
What You’ll Need
Master’s or Ph.D. in Computer Science, Statistics, Engineering, or a highly quantitative field.
12+ years of progressive experience in data science, with at least 5‑7 years in a senior leadership role (VP or SVP level) managing global, production‑focused ML/AI teams.
Deep, hands‑on expertise in the full machine learning lifecycle. Proven experience with advanced techniques like deep learning, NLP/Generative AI, and predictive time‑series modeling, specifically applied to financial, claims, or clinical data.
Demonstrable success translating complex business challenges into clear, deliverable, and high‑ROI data science roadmaps.
Proven track record of successfully applying data science to both clinical and financial/RCM data (e.g., EHR data, claims, remittances) to drive measurable outcomes is preferred.
About Waystar Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle. Waystar’s healthcare payments platform combines innovative, cloud‑based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities.
WAYSTAR PERKS
Competitive total rewards (base salary + bonus, if applicable)
Customizable benefits package (3 medical plans with Health Savings Account company match)
Generous paid time off: 3 weeks + 13 paid holidays for non‑exempt; 13 paid holidays for exempt; additional personal floating holidays.
Paid parental leave (including maternity & paternity)
Education assistance; free LinkedIn Learning access
Free mental health and family planning programs, including adoption assistance and fertility support
401(k) program with company match
Pet insurance
Employee resource groups
Equal Opportunity Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
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About This Position Waystar is a market-leading provider of cloud-based healthcare payments software. Our mission-critical platform simplifies the complex revenue cycle for providers, enabling them to get paid faster and more accurately, and focus on patient care. We process billions of transactions annually, leveraging a massive dataset of claims, remittances, and patient data to drive outcomes. With Waystar AltitudeAI™, we are at the forefront of applying AI, generative AI, and advanced automation to transform healthcare finance, reduce administrative burden, and achieve peak financial performance for our clients.
What You’ll Do As the VP of Data Science, you will be a strategic and technical leader reporting directly to the SVP of Data Science + Analytics. Your primary responsibility will be to establish and execute the data science strategy that underpins the evolution of the Waystar AltitudeAI™ platform. This role demands a visionary who can lead a world-class team, driving innovation to solve the most critical challenges in healthcare revenue cycle management (RCM)—from preventing denials and optimizing prior authorizations to delivering transparent patient financial experiences. You must possess deep technical expertise in machine learning, including foundation models, and have consistently delivered production-grade, highly available solutions that yield quantifiable improvements in customer outcomes in complex, regulated environments.
Strategic Leadership & Healthcare Innovation
Develop and champion a comprehensive data science and ML strategy that directly translates into new product capabilities and significant business value for Waystar and its clients, focusing on using data to predict, prevent, and automate RCM workflows.
Establish and steward a portfolio of model types—classification, regression, ranking, forecasting, NLP/LLMs, anomaly detection—that address both clinical and financial objectives.
Integrate heterogeneous model outputs (clinical insights, operational predictions, financial risk scores) into an integrated, governed enterprise data set that supports analytics, product experiences, and downstream decisioning.
Collaborate closely with product, engineering, and commercial leaders to embed data science and ML into core platform offerings, ensuring technical initiatives align with market needs and HIPAA/security compliance.
Spearhead research and deployment of cutting‑edge AI and generative AI solutions—such as using LLMs for policy document interpretation and predictive modeling for claim denial rates—to create differentiated, proprietary technology.
Act as a thought leader with analysts, customers, and prospects; communicate our approach, differentiation, and evidence of impact.
Leading Data Science Teams & MLOps
Attract, mentor, and scale a high‑performing, geographically distributed team of Data Scientists and Machine Learning Engineers, fostering a culture of technical excellence, accountability, and continuous learning.
Define and enforce best practices for the entire machine learning lifecycle in a regulated environment, including robust model governance, versioning, continuous monitoring, and drift detection to ensure accuracy and compliance of all production models.
Ensure the team operates with the highest standards of data governance, privacy (HIPAA), and algorithmic fairness, specifically addressing bias and transparency in models impacting provider finances and patient care.
Technical Expertise in Machine Learning Principles and Healthcare Data
Act as the ultimate technical authority on machine learning principles, statistical rigor, and large‑scale data analysis within the company.
Demonstrated experience and deep theoretical understanding of foundation models (LLMs, VLMs), including model selection, fine‑tuning techniques (LoRA, QLoRA), Retrieval‑Augmented Generation (RAG) implementation, and prompt engineering for generating accurate, context‑aware outputs in a healthcare setting.
Expertise in advanced machine learning algorithms—XGBoost, CNNs, RNNs, Transformer architectures.
Deep familiarity with NLP approaches—concept extraction, human language understanding, summarization—particularly in clinical and healthcare contexts.
Working knowledge of Python, PyTorch, and TensorFlow for developing and scaling machine learning solutions.
Direct the technical architecture and tools used for all data science initiatives, leveraging cloud‑native solutions (AWS, GCP) and distributed computing frameworks to handle Waystar’s massive, multi‑petabyte datasets.
Oversee the design of rigorous A/B testing and experimentation frameworks to accurately measure the clinical and financial impact of deployed ML models on client RCM performance.
What You’ll Need
Master’s or Ph.D. in Computer Science, Statistics, Engineering, or a highly quantitative field.
12+ years of progressive experience in data science, with at least 5‑7 years in a senior leadership role (VP or SVP level) managing global, production‑focused ML/AI teams.
Deep, hands‑on expertise in the full machine learning lifecycle. Proven experience with advanced techniques like deep learning, NLP/Generative AI, and predictive time‑series modeling, specifically applied to financial, claims, or clinical data.
Demonstrable success translating complex business challenges into clear, deliverable, and high‑ROI data science roadmaps.
Proven track record of successfully applying data science to both clinical and financial/RCM data (e.g., EHR data, claims, remittances) to drive measurable outcomes is preferred.
About Waystar Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle. Waystar’s healthcare payments platform combines innovative, cloud‑based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities.
WAYSTAR PERKS
Competitive total rewards (base salary + bonus, if applicable)
Customizable benefits package (3 medical plans with Health Savings Account company match)
Generous paid time off: 3 weeks + 13 paid holidays for non‑exempt; 13 paid holidays for exempt; additional personal floating holidays.
Paid parental leave (including maternity & paternity)
Education assistance; free LinkedIn Learning access
Free mental health and family planning programs, including adoption assistance and fertility support
401(k) program with company match
Pet insurance
Employee resource groups
Equal Opportunity Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
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