Data Scientist II

Cohere Health; United States; Remote; USD 137,000 - 161,000; Full time

Job summary

Cohere Health, Inc. in Boston, Massachusetts (Remote) is seeking a Data Scientist II for a fully remote role within the United States.

This position may be performed from anywhere in the U.S., with occasional travel to the company headquarters for onboarding, team meetings, and events. Duties include gathering business requirements, analyzing healthcare claims and SDoH data to identify trends, applying LLMs and NLP techniques, building scalable data pipelines, and creating dashboards to support

Qualifications

• Master’s degree in Data Science, Statistics, Biostatistics or related field with 36 months of analytics experience.
• Three years of experience analyzing healthcare datasets (EMR/EHR, claims, SDoH).
• Experience building scalable AWS Airflow pipelines with Python and PySpark on AWS S3 and SageMaker.
• Experience with regression analysis, outlier detection, and NLP/LLMs and model development.

Responsibilities

• Gather business requirements and analyze trends to provide actionable insights.
• Analyze healthcare claims and authorization data to identify outliers and trends.
• Apply LLMs, stochastic optimization methods, and related technologies to support decision-making.
• Monitor industry trends, regulatory changes, and emerging fraud schemes to support strategy development.
• Train, fine-tune, and implement LLMs and deep learning models for anomaly detection and classification.
• Develop data models, algorithms, and simulations to support analytical objectives.
• Build visualizations and dashboards to communicate findings and support business workflows.

Skills

EMR/EHR data

Data quality analysis

Python

PySpark

AWS

Airflow

Tableau

NLP

LLMs

Model development

Education

Master's degree in Data Science / Statistics / Biostatistics

Tools

Python

PySpark

AWS Sagemaker

Tableau

SQL

Spark

Airflow

Job description

Data Scientist II, Cohere Health, Inc., Boston, Massachusetts (Remote)

This is a fully remote position and may be performed from anywhere within the United States. Occasional travel to company headquarters in the U.S. for onboarding, team meetings, and company events may be required.

Duties

Gather business requirements and apply trend analysis to identify actionable insights using analytic tools. 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 decision-making. Monitor industry trends, regulatory changes, and emerging fraud schemes to support detection strategy development, maintain methodology documentation, and present findings to leadership. Train, fine-tune, and implement LLMs and deep learning models for tasks such as 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 to communicate analytical findings and support business workflows.

Requirements

• Must have a Master’s degree in Data Science, Statistics, Biostatistics or related field (willing to accept foreign education equivalent) and 36 months of experience as Analyst or related position analyzing datasets.
• Must possess three (3) years of experience (may be gained concurrently with above experience) in the following skills:
• 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 and AWS S3 storage, and accelerate business decision-making in AWS Sagemaker;
• Utilizing trend identification and data analysis methods such as regression analysis and outlier detection model in python, spark and sql.;
• Building and implementing models, creating algorithms, and running simulations;
• Developing Tableau visualization and partnering with product owners and stakeholders to drive enterprise-level solutions that integrate data science into business workflows;
• Developing NLP, LLMs (extractive and generative), fine-tuning, and LLM model development.

Salary range is $137,000.00 to $161,000.00 per year for a 40-hour work week.

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