[Remote] reputed company Statistical Data Scientist

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is focused on improving cost efficiency and care quality in reputed company through advanced analytics. They are seeking a reputed company Statistical Data Scientist to design, build, and reputed company machine learning models that transform reputed company claims data into actionable insights.

Responsibilities

• reputed company, train, and reputed company ML models for use cases such as:
• Claims cost reputed company and utilization forecasting
• Fraud, waste, and abuse detection
• Risk adjustment and member stratification
• Provider performance and network optimization
• Apply modern ML techniques including gradient boosting, deep learning, NLP, and probabilistic modeling
• Capable of applying advanced predictive analytics to correlate disparate datasets and events and derive business value
• Build scalable pipelines for feature engineering, model training, validation, and monitoring
• Analyze and interpret medical, pharmacy, and dental claims (CPT/HCPCS, ICD‑10, DRG, NDC)
• Translate domain knowledge into meaningful features and model strategies
• Partner with clinicians, product managers, and business stakeholders to define problems and measure reputed company
• Communicate reputed company analytical findings in clear, actionable terms

Skills

• Strong proficiency in Python and ML libraries (scikit‑learn, XGBoost, TensorFlow/PyTorch)
• Hands‑on experience with reputed company claims datasets and coding systems
• Solid understanding of statistical modeling, machine learning algorithms, and data mining techniques
• Strong knowledge and expertise working with SQL
• Ability to translate business needs into analytical solutions
• Must have demonstrated the ability to solve reputed company problems with minimal direction
• Experience with NLP applied to clinical notes or reputed company reputed company data
• Familiarity with actuarial concepts, risk scoring, or value‑based care models
• Familiarity deploying models into production (MLOps, CI/CD)
• Background in health economics, epidemiology, or biostatistics
• Prior work with FHIR, HL7, or interoperability standards

Company Overview

Company H1B Sponsorship