Cube Hub Inc.Remote
Data Scientist – Healthcare & Pharma Commercial Analytics (AI/ML & GenAI)
United States of America
Full Time
4 hours ago
No H1B
Key skills
Data ScienceMachine LearningPythonSQLPredictive ModelingClassificationRegressionClusteringNatural Language ProcessingHealthcare Data AnalysisPharmaceutical Commercial AnalyticsLarge Language ModelsPrompt EngineeringRetrieval-Augmented GenerationAI Agent FrameworksVector DatabasesAPI-based AI IntegrationsDatabricksAWS SageMakerAzure MLModel DeploymentModel MonitoringDockerREST APIsCI/CD PipelinesMLOpsAIMLNLPGenAIRAGLangChainAutoGenData EngineeringAnalyticsBITableauPower BIAWSAzureSageMakerCRMCI/CDLeadershipSales
About this role
Cube Hub Inc. is seeking a highly motivated Data Scientist to join their Global Data & Digital Innovation team focused on pharmaceutical commercial analytics. The role involves developing AI and machine learning solutions to enhance commercial effectiveness and improve healthcare professional engagement.
Responsibilities:
- Develop and deploy predictive models for patient events, including therapy initiation, adherence, and line-switch prediction
- Design and scale Next Best Action (NBA) solutions to optimize HCP engagement strategies
- Build advanced machine learning models using regression, classification, and NLP techniques
- Develop customer journey analytics and multi-touch attribution models
- Integrate GenAI capabilities into commercial workflows, including:
- HCP engagement planning
- Content personalization
- AI-powered decision support systems
- GenAI interfaces for ML solutions
- Build and maintain end-to-end ML pipelines, including data ingestion, feature engineering, model training, deployment, monitoring, and retraining
- Implement MLOps best practices, CI/CD processes, and model governance
- Partner with Sales, Marketing, Commercial Analytics, and Data Engineering teams to translate business needs into scalable analytical solutions
- Present insights and recommendations to business stakeholders and leadership
Requirements:
- Master's or PhD in Data Science, Computer Science, Statistics, Mathematics, Operations Research, or a related quantitative discipline
- 5+ years of Data Science, Machine Learning, or Advanced Analytics experience (or 3+ years with a PhD)
- Strong proficiency in Python and SQL
- Experience with machine learning techniques including predictive modeling, classification, regression, clustering, and NLP
- Experience working with healthcare datasets such as Claims, EHR/EMR, CRM, and digital engagement data
- Knowledge of pharmaceutical or healthcare commercial analytics
- Hands-on experience with Large Language Models (LLMs)
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agent frameworks such as LangChain, AutoGen, MCP, or A2A
- Familiarity with vector databases, embeddings, and API-based AI integrations
- Experience with Databricks, AWS SageMaker, Azure ML, or similar platforms
- Knowledge of model deployment, monitoring, Docker, REST APIs, and CI/CD pipelines
- Experience building scalable production-grade ML solutions
- Pharmaceutical commercial analytics
- Patient journey analytics
- HCP targeting and segmentation
- Omnichannel marketing analytics
- Sales force effectiveness
- Next Best Action (NBA) frameworks
- Promotional response modeling and multi-touch attribution
- Databricks
- AWS SageMaker
- Azure ML
- Power BI
- Tableau
- LangChain
- AutoGen