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Salary: USD 137,000 - 161,000 / annual
Cohere Health is seeking a Data Scientist II to drive analytical insights and support decision-making across healthcare operations. In this fully remote role, you will gather business requirements and apply trend analysis to identify actionable insights using advanced analytic tools.
Key responsibilities include:
- Analyze healthcare claims and authorization data to identify outliers, interpret patterns, and assess trends and opportunities
- Apply large language models (LLMs), stochastic optimization methods, and related technologies to support strategic decision-making
- Monitor industry trends, regulatory changes, and emerging fraud schemes to support detection strategy development
- Train, fine-tune, and implement LLMs and deep learning models for anomaly detection, classification, and automated analysis of security-related or operational data
- Analyze datasets to assess expected impacts and return on investment, including effects on medical expense, administrative cost, and clinical outcomes
- Develop data models, algorithms, and simulations to support analytical objectives
- Build visualizations and dashboards using Tableau to communicate findings and support business workflows
- Maintain methodology documentation and present findings to leadership
Occasional travel to company headquarters in the U.S. for onboarding, team meetings, and company events may be required.
Requirements:
- Master's degree in Data Science, Statistics, Biostatistics, or related field (foreign education equivalent acceptable)
- 36 months of experience as an Analyst or related position analyzing datasets
- 3+ years of experience in the following areas (may overlap with above):
- Analyzing healthcare datasets, including EMR/EHR data, medical and pharmacy claims data, and Social Determinants of Health (SDoH) data
- Performing data quality analysis to identify data quality issues, gaps, or inconsistencies
- Building scalable AWS Airflow pipelines to ingest, integrate, and transform terabytes of data using Python and PySpark with AWS S3 storage and AWS SageMaker
- Utilizing trend identification and data analysis methods such as regression analysis and outlier detection models in Python, Spark, and SQL
- Building and implementing models, creating algorithms, and running simulations
- Developing Tableau visualizations and partnering with product owners and stakeholders to drive enterprise-level solutions
- Developing NLP, LLMs (extractive and generative), fine-tuning, and LLM model development
