[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