SpectraMedix is at the forefront of transforming healthcare, empowering health plans and health systems with the tools and insights they need to provide better, more cost-effective care to the communities they serve. Our cutting-edge platform delivers advanced analytics that help organizations excel in the transition to new value-based payment (VBP) models.
By combining advanced technology with a team of seasoned experts, we provide a unique solution tailored to meet the needs of the healthcare industry during this critical phase of value-based care evolution. Our platform is strategically designed to guide health plans, accountable care organizations, and health systems in their journey toward achieving success in value-based payment initiatives.
We are committed to creating an environment where innovation thrives, employees are empowered to drive meaningful change, and every team member plays a key role in reshaping the value and quality equation in healthcare. Our organization’s long-term stability is grounded in this commitment, and we prioritize our employees' growth, well-being, and success as the foundation for a thriving future—both for them and for the communities we serve.
Location: Hybrid(NJ)
Roles and Responsibilities:
- Data Governance and Administration: Own VBC reporting administration, data integrity, and compliance workflows to ensure reliable metrics.
- Healthcare Data Analysis: Analyze medical claims, clinical records, and population health data to measure performance against VBC goals like total cost of care and quality metrics.
- Cross-Functional Collaboration: Partner with clinical, finance, product, and engineering teams to align data insights with organizational and client objectives.
- Product Development: Support building of interactive dashboards, scorecards, and ad-hoc reports using BI tools like Tableau and/or SaaS platforms.
- Actionable Insights Delivery: Translate technical findings into plain-language business recommendations for non-technical stakeholders and executive leadership.
Demonstrable AI knowledge:
- AI & ML Literacy: Understanding foundational AI/ML concepts and how they apply to healthcare reporting analytics.
- AI Tool Integration: Collaborate with data scientists to embed ideas directly into the reports and dashboards.
- Prompt Engineering: Leverage generative AI assistants to accelerate SQL query writing, automate documentation, and build prototype data models.
- Executive Storytelling: Synthesize intricate technical and statistical findings into plain-language business recommendations for internal leadership.
Requirements & Qualifications
Technical Skills & Tools
- Database Querying: Expert-level SQL proficiency for data extraction, manipulation, and optimization.
- Programming & Scripting: Strong competency in Python or R to manipulate data, connect to AI APIs, and evaluate model evaluation metrics (e.g., ROC/AUC curves).
- Business Intelligence: Advanced knowledge of Power BI or Tableau, specifically utilizing native AI plugins (e.g., automated key influencers, smart narratives).
- AI Productivity: Experience using generative AI coding assistants (e.g., GitHub Copilot) to accelerate query writing and documentation.
Domain Knowledge & Experience
- Value-Based Care Expertise: Strong understanding of VBC reimbursement frameworks (e.g., ACOs, Capitation, Bundled Payments) and risk adjustment methodologies (e.g., CMS-HCC model).
- Regulatory Knowledge: Familiarity with healthcare quality rating systems (HEDIS, MIPS) and absolute compliance with HIPAA regulations regarding Protected Health Information (PHI).
- Experience: 6-8+ years of experience as a data analyst within a healthcare payer, provider, or specialized health-tech vendor organization.
Preferred Qualifications
- Experience with cloud data warehouses (e.g., Snowflake, Databricks, AWS).
- Basic understanding of machine learning frameworks (e.g., scikit-learn).
- Bachelor’s or Master's degree in Health Informatics, Data Science, Statistics, Economics, or a related quantitative field.
- Strong verbal and written communication, technical articulation, listening, and presentation skills are essential
- Should have proven analytical and problem-solving skills
- Demonstrated expertise in prioritization, time management, and stakeholder management (both internal and external) is necessary
- Should be a quick learner, self-starter, proactive, and an effective team player
- Must have experience working under tight deadlines within a matrix organizational structure