What are the responsibilities and job description for the Data Scientist - Advanced Analytics in Healthcare position at Newscape Consulting LLP?
Data Scientist (Healthcare Payor Market & Python Engineering)
About the Role
We are seeking a highly skilled Data Scientist with deep expertise in the healthcare payor market and advanced proficiency in Python engineering. This role will focus on leveraging data science techniques to extract insights, develop predictive models, and drive analytics-driven decision-making for healthcare payors. The ideal candidate will have experience working with healthcare claims, provider networks, risk adjustment, and payment integrity, as well as a strong technical background in data wrangling, feature engineering, and model deployment.
Key Responsibilities
- Data Engineering & Wrangling: Collect, clean, and preprocess large healthcare datasets, including claims, eligibility, provider, and reimbursement data.
- Model Development: Design and implement machine learning models to address fraud detection, payment integrity, risk scoring, and utilization trends.
- Healthcare Analytics: Develop advanced analytics to improve cost efficiency, provider performance, and payer reimbursement strategies.
- Python Development: Build scalable data pipelines and automation scripts for model training, deployment, and monitoring.
- Statistical & Predictive Modeling: Apply advanced statistical techniques, predictive modeling, and AI/ML methodologies to generate actionable insights.
- Data Visualization & Reporting: Develop dashboards and reports using Python, Power BI, or Tableau to present findings to stakeholders.
- Collaboration & Communication: Work cross-functionally with product teams, actuarial analysts, engineers, and business leaders to translate business needs into data-driven solutions.
- Regulatory & Compliance Awareness: Ensure models align with CMS, HIPAA, and healthcare regulatory frameworks.
Required Qualifications
- Experience: At least 3 years of experience in 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
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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
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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**
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- 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.
Job Types: Full-time, Contract
Pay: $60,351.00 - $70,456.00 per year
Work Location: In person
Salary : $60,351 - $70,456