Note: The job is a remote job and is open to candidates in USA. RED Global is seeking an experienced Principal Data Scientist with Healthcare/Life Sciences expertise. The role supports the design and delivery of advanced analytics, machine learning, and AI solutions, taking ML solutions from experimentation through production while advising clinical, technical, and executive stakeholders.
Responsibilities
- Support the design and delivery of advanced analytics, machine learning, and AI solutions
- Take ML solutions from experimentation through production
- Advising clinical, technical, and executive stakeholders
Skills
- 10+ years of experience across Data Science, Machine Learning, AI, healthcare analytics, or enterprise data platforms
- Strong Healthcare / Life Sciences experience, including clinical data, patient data, provider environments, healthcare operations, population health, or related HLS use cases
- Deep hands-on experience with Azure Machine Learning, including experimentation, model training, model registry, deployment, monitoring, evaluation, and lifecycle management
- Strong hands-on Databricks experience, including notebooks, feature engineering, MLflow, Delta Lake, and scalable data pipelines
- Strong applied machine learning experience across predictive modeling, NLP, classification, regression, clustering, feature engineering, experiment design, and model validation
- Experience taking ML solutions from development through production deployment and operationalization
- Strong MLOps experience, including CI/CD, version control, model registry, reproducibility, monitoring, and governance
- Experience assessing clinical and operational data quality, feature readiness, lineage, and data gaps
- Understanding of Responsible AI, including model explainability, bias, safety, drift, auditability, and governance within PHI-sensitive environments
- Ability to translate clinical and business problems into scalable data science and ML solutions
- Strong client-facing consulting and executive communication skills, with the ability to advise stakeholders on AI/ML strategy, risks, tradeoffs, and adoption
- Experience mentoring data scientists/engineers and establishing reusable ML patterns and delivery best practices
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