Data Scientist, Consultant

Your Role The Advanced Analytics team partners across the entire Blue Shield of CA enterprise to accelerate business outcomes through AI/machine learning, statistical methodologies, and unstructured data analysis. The Data Scientist, Consultant will report to the Director, Advanced Analytics. You will solve problems such as text analytics of customer feedback, clinical notes, predicting disease progression, analyzing population health programs, clustering behaviors, creating propensity models, and geospatial analysis to uncover social determinants of health. Your Knowledge and Experience Bachelor's degree in mathematics, statistics, computer science, or a related quantitative field At least 3 years of professional Data Science or ML experience, or a Ph.D. in a quantitative discipline Ability to translate business problems into ML solutions and communicate AI recommendations to non-technical audiences Proficiency in scalable data transformation using SQL, SAS, Spark, or similar Proficiency in Python, R, and Julia Experience with cloud platforms such as Azure and Google Cloud; familiarity with DataBricks is a plus Knowledge of statistical methods and advanced modeling techniques (e.g., SVM, K-Means, Random Forest, Boosting, Bayesian inference, NLP) Experience with machine learning and deep learning frameworks (scikit-learn, XGBoost, TensorFlow, PyTorch) Understanding of model evaluation metrics including fairness, bias, accuracy, drift, validity, robustness, and explainability MLOps experience including documentation, testing, and version control (git) Experience in experimental design and A/B testing Knowledge of Generative AI techniques and applications, such as natural language generation, image synthesis, and content creation Experience with Generative AI frameworks like GPT, GANs, and VAEs Ability to develop and deploy generative models for various applications Understanding of ethical considerations in Generative AI deployment Strong collaboration and stakeholder engagement skills across diverse teams

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