Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global professional services organization is seeking a Payer Healthcare Data Scientist, Manager to support healthcare organizations through advanced data science, machine learning, and operations consulting. The role focuses on analyzing complex healthcare data, developing actionable insights, and helping payer organizations improve operational efficiency, reduce costs, and enhance population health outcomes.
The successful candidate will combine strong technical expertise in data science and machine learning with consulting, leadership, and client management capabilities. The position offers opportunities to collaborate with healthcare industry leaders and contribute to innovative analytics solutions that address complex payer challenges.
The role involves applying advanced analytical methodologies to large-scale claims, clinical, and member datasets. The successful candidate will also lead teams, manage client relationships, mentor junior professionals, and help deliver strategic solutions while maintaining high standards of quality and integrity.
Leadership and Professional Expectations
- Analyze and identify linkages and interactions between the component parts of complex systems.
- Take ownership of projects, ensuring successful planning, budgeting, execution, and completion.
- Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
- Develop skills beyond existing areas of expertise and encourage team members to do the same.
- Effectively mentor and develop other professionals.
- Use work reviews as opportunities to deepen the expertise of team members.
- Address conflicts and issues effectively, including engaging in difficult conversations with clients, team members, and other stakeholders when appropriate.
- Uphold professional and technical standards, organizational codes of conduct, and applicable independence requirements.
- Lead with integrity and authenticity while promoting innovation and continuous improvement.
- Embrace technology and innovation to enhance client delivery and business outcomes.
Key Responsibilities
- Apply advanced data science and machine learning methodologies to analyze large-scale claims and clinical datasets.
- Generate actionable insights aimed at reducing healthcare costs and improving population health outcomes.
- Lead and mentor data science teams while managing client relationships and expectations.
- Manage successful project execution while maintaining rigorous quality standards.
- Collaborate with healthcare industry leaders to develop innovative analytics solutions.
- Present analytical findings, recommendations, and strategies to senior stakeholders, including Chief Actuaries.
- Contribute to the development of new analytics products supporting payer strategies.
- Foster a culture of continuous improvement, knowledge sharing, and professional development.
- Apply analytical techniques to identify trends, opportunities, and risks within healthcare data.
- Support strategic decision-making through data-driven recommendations.
Required Qualifications
- Bachelor’s degree.
- At least 6 years of experience in data science and machine learning.
- Strong experience analyzing large and complex datasets.
- Demonstrated ability to apply advanced data science methodologies to business problems.
- Strong leadership, mentoring, communication, and project management capabilities.
- Ability to work effectively with clients and senior stakeholders.
- Experience translating complex analytical findings into actionable business recommendations.
Preferred Qualifications
- Master’s degree in Statistics, Computer Science, Applied Mathematics, Biotechnology, or a related field.
- Prior experience with consulting or advisory firms.
- Experience contributing to commercial analytics product development.
- Familiarity with NCQA HEDIS specifications and CMS Star Ratings.
- Knowledge of government payer programs and Medicaid.
- Experience working with natural language processing (NLP) or unstructured clinical text.
- Exposure to integrating social determinants of health data.
- Experience developing analytics solutions for healthcare payers.
- Knowledge of healthcare claims, clinical, and member data.
- Experience working with machine learning models and advanced analytical techniques.
Disclaimer
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