Role overview
As a Data Scientist at PMMC, you will design, develop, and deploy advanced analytical, machine learning, and generative AI solutions that drive financial and operational improvements for healthcare organizations. You will work with large-scale, complex healthcare revenue cycle datasets to uncover actionable insights, forecast trends, and identify opportunities to improve outcomes.
You will work closely with data science, engineering, BI, and product teams to translate business needs into analytical frameworks, build robust models and GenAI workflows, and operationalize intelligence within PMMC’s solutions.
What you'll work on
- Lead complex machine learning, statistical modeling, and GenAI initiatives from ideation to production deployment to support revenue cycle optimization.
- Use advanced EDA techniques to discover trends, identify performance drivers, and generate actionable insights.
- Translate business questions into analytical approaches and collaborate cross-functionally to deliver data-driven recommendations.
- Drive innovation and influence strategic initiatives by identifying new opportunities for advanced analytics, AI, automation, and predictive intelligence to shape PMMC’s data and AI roadmap and enhance our product suite.
- Create clear visualizations, dashboards, and reports to communicate insights to stakeholders at all levels.
- Document data sources, methodologies, assumptions, and model architectures for technical and compliance purposes.
What we're looking for
- Master’s degree with 1-5 years of experience
- OR PhD with 1-3 years of experience in data science, ML engineering, or advanced analytics.
- Proficiency in Python, SQL, and data science libraries such as pandas, NumPy, scikit-learn, and stats models.
- Experience developing and evaluating machine learning models and foundational generative AI/LLM applications, including prompt engineering or fine-tuning.
- Strong analytical and problem-solving skills with experience working with large or complex datasets.
- Ability to translate business needs into analytical solutions and communicate findings to both technical and non-technical audiences.
- Ability to work independently in fast-paced environments with multiple ongoing projects.
- Strong communication skills and proven ability to collaborate with stakeholders across product, engineering, and leadership teams.
Tags & focus areas
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