Data Scientist, Consultant

Your Role

The Advanced Analytics team works in partnership across the entire Blue Shield of CA enterprise to accelerate business outcomes through the application of AI/machine learning, statistical methodologies, or unstructured data analysis techniques to uncover insights, predict behaviors, and ultimately drive automation to create “intelligence at scale”. The Data Scientist, Consultant will report to the Director, Advanced Analytics. In this role you will solve problems which range from but are not limited to, text analytics of customer feedback, conversations, and clinical notes, predicting clinical disease progression, understanding the impact of population health programs, clustering member behaviors, creating propensity models, and geospatial analysis of populations to uncover social determinants of health.

Your Work

In this role, you will:

• Collaborate with product owners and business stakeholders to identify opportunities for process optimization and decision-making improvements
• Perform data exploration and visualization using Python on DataBricks, Tableau, and Python Notebooks to understand the signal-to-noise ratio in datasets
• Partner with the data engineering team for rapid prototyping of training data sets using SQL, Apache Spark, and other tools
• Conduct feature engineering using appropriate techniques for the given data and business problem
• Develop robust model validation procedures and generate performance metrics for evaluation and monitoring
• Act as the subject matter expert in applied ML for claims, premiums, member risk scores, and other business contexts
• Drive the lifecycle of machine learning projects from ideation to deployment, ensuring timely delivery and maintaining documentation
• Perform literature reviews to inform statistical modeling approaches and best practices
• Translate business requirements into technical specifications and design scalable pipelines with data engineers
• Assist in transitioning from on-prem infrastructure to the cloud
• Convert text-based data into feature data sets for predictive analytics
• Develop materials to explain project findings
• Lead and contribute to Generative AI projects, including model development and deployment for applications like natural language generation and image synthesis
• Stay updated with advancements in Generative AI and incorporate relevant techniques into projects
• Collaborate with cross-functional teams to integrate Generative AI solutions into products and services
• Conduct experiments and research to explore new applications of Generative AI in healthcare
• Provide mentorship on Generative AI techniques and best practices
• Perform other projects or duties as assigned

Your Knowledge and Experience

• Requires a bachelor’s degree in mathematics, statistics, computer science, or an equivalent quantitative scientific discipline
• Requires at least 3 years of professional Data Science or ML experience; or a Ph.D. degree in operations research, applied statistics, data mining, machine learning, or other quantitative discipline
• Must be able to demonstrate real-world experience to translate business problems into an ML problem and be able to communicate AI recommendations in a business context to a general non-technical audience
• Proficiency in scalable data transformation techniques using SQL, SAS, Spark, or equivalent
• Proficiency in open-source languages such as Python, R, and Julia
• Hands-on experience with cloud environments such as Azure and Google Cloud and nice to have experience in DataBricks
• Understanding of statistical methods and advanced modeling techniques (e.g., SVM, K-Means, Random Forest, Boosting, Bayesian inference, natural language processing)
• Experience with machine learning and deep learning packages (scikit-learn, XGBoost, Tensorflow, or PyTorch)
• Knowledge of evaluating solutions for fairness, bias, accuracy, drift, validity, fit, robustness, and explainability
• MLOps experience including good design documentation, unit testing, integration testing, and version control (git)
• Experience in experimentation design and A/B testing
• Knowledge and experience in Generative AI techniques and applications, including natural language generation, image synthesis, and automated content creation
• Experience with Generative AI frameworks and tools such as GPT, GANs, and VAEs
• Ability to develop and deploy generative models for various applications
• Understanding of ethical considerations and best practices in the development and deployment of Generative AI solutions
• Ability to partner, collaborate with, and lead relevant stakeholders across diverse functions and experience levels