Sr. Manager, Data Science

ABOUT THIS POSITION

As the Sr Manager, Data Science, you will be a technical and operational leader reporting to the VP of Data Science. Your primary responsibility will be to lead a team of data scientists, driving the development and deployment of innovative data science solutions that support Waystar’s AltitudeAI™ platform and healthcare revenue cycle management (RCM) products. This role requires strong hands-on expertise in machine learning, a passion for mentoring, and the ability to deliver production-grade solutions that improve customer outcomes in a regulated environment.

WHAT YOU'LL DO

Team Leadership & Project Execution

• Lead, mentor, and develop a team of data scientists, fostering a culture of technical excellence, collaboration, and continuous learning.

• Manage day-to-day operations of data science projects, ensuring timely delivery and alignment with business objectives.

• Oversee the implementation and monitoring of machine learning models, ensuring accuracy, compliance, and reliability in production settings.

• Collaborate with product, engineering, and analytics teams to integrate data science solutions into core platform offerings.
   

Technical Execution & Innovation

• Apply advanced machine learning techniques (classification, regression, clustering, NLP, LLMs, anomaly detection) to solve business and clinical challenges in healthcare RCM.

• Develop and maintain robust model governance processes, including versioning, monitoring, and drift detection.

• Support the evaluation and adoption of new technologies and tools to enhance data science capabilities.

• Participate in the design and execution of A/B tests and experiments to measure the impact of deployed models.

Collaboration & Communication

• Communicate technical findings and project status to stakeholders, including product managers and engineering leads.

• Contribute to the development of technical documentation and best practices for the data science team.

• Support the team’s professional development through coaching, training, and knowledge sharing.

WHAT YOU'LL NEED

• Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related quantitative field.

• 7+ years of experience in data science or machine learning, with at least 2 years in a leadership or team lead role.

• Hands-on expertise in the full machine learning lifecycle, including model development, deployment, and monitoring.

• Experience with deep learning, NLP, and generative AI techniques (e.g., transformers, LLMs) preferred.

• Strong programming skills in Python and familiarity with ML frameworks (PyTorch, TensorFlow, XGBoost).

• Experience working with healthcare, financial, or claims data is a plus.

• Excellent communication and collaboration skills.

WAYSTAR PERKS

• Competitive total rewards (base salary + bonus, if applicable)
• Customizable benefits package (3 medical plans with Health Saving Account company match)
• We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
• Paid parental leave (including maternity + paternity leave)
• Education assistance opportunities and 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

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.