Data Scientist

• Experience: 5+ years in data science, machine learning, and Python-based data engineering within the healthcare payor space.
• Technical Skills:
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, Flask/FastAPI)
• Experience with SQL and NoSQL databases (PostgreSQL, Snowflake, BigQuery, MongoDB, etc.)
• Hands-on experience with ETL processes, data pipelines, and cloud platforms (AWS, GCP, or Azure)
• Knowledge of Big Data technologies (Spark, Databricks, or Hadoop) is a plus
• Domain Expertise: Deep understanding of claims processing, risk adjustment, provider reimbursement models, and fraud detection.
• Machine Learning & AI: Experience developing supervised and unsupervised models, NLP applications, and anomaly detection algorithms.
• Data Governance & Security: Understanding of HIPAA, CMS regulations, and healthcare compliance requirements.
• Soft Skills: Strong analytical mindset, problem-solving abilities, and the ability to communicate complex insights to non-technical stakeholders.

Preferred Qualifications

• Experience with FHIR, HL7, or other healthcare interoperability standards.
• Familiarity with payer-provider data exchange models and value-based care analytics.
• Experience working with CMS claims data, MCO data, or Medicare Advantage risk models.