... optimal data architecture leveraging structured and unstructured data. • Establish and govern ... Bayesian inference, predictive modeling, supervised/unsupervised/deep learning Natural language ...
... optimal data architecture leveraging structured and unstructured data. • Establish and govern ... Bayesian inference, predictive modeling, supervised/unsupervised/deep learning Natural language ...
Director, Data Science
Chicago, IL · Hybrid
Diminishing returns curves, budget optimization, and scenario planning * Custom causal inference ... Proficiency in statistical modeling and a working understanding of Bayesian and frequentist ...
Director, Data Science
Chicago, IL · Hybrid
Diminishing returns curves, budget optimization, and scenario planning * Custom causal inference ... Proficiency in statistical modeling and a working understanding of Bayesian and frequentist ...
Director, Data Science
Chicago, IL · On-site
Diminishing returns curves, budget optimization, and scenario planning * Custom causal inference ... Proficiency in statistical modeling and a working understanding of Bayesian and frequentist ...
Director, Data Science
Chicago, IL · On-site
Diminishing returns curves, budget optimization, and scenario planning * Custom causal inference ... Proficiency in statistical modeling and a working understanding of Bayesian and frequentist ...
Bayesian Optimization information
What is the difference between Bayesian Optimization vs Data Scientist?
| Aspect | Bayesian Optimization | Data Scientist |
|---|---|---|
| Primary Focus | Optimizing complex functions and hyperparameters | Analyzing data, building models, deriving insights |
| Required Skills | Statistics, probability, machine learning, programming | Statistics, programming, data analysis, visualization |
| Work Environment | Research labs, AI/ML teams, R&D departments | Business, tech companies, consulting firms |
| Common Tools | Python, R, Bayesian libraries (e.g., GPy, scikit-optimize) | Python, R, SQL, visualization tools |
Bayesian Optimization is a specialized technique used within machine learning and AI to efficiently tune hyperparameters or optimize functions. Data Scientists often utilize Bayesian Optimization as part of their toolkit but have broader responsibilities, including data analysis, modeling, and reporting. While Bayesian Optimization focuses on optimization tasks, Data Scientists work on understanding and interpreting data to inform business decisions.
What are popular job titles related to Bayesian Optimization jobs in Illinois? For Bayesian Optimization jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Bayesian Optimization jobs in Illinois look for? The top searched job categories for Bayesian Optimization jobs in Illinois are:
What cities in Illinois are hiring for Bayesian Optimization jobs? Cities in Illinois with the most Bayesian Optimization job openings:
Full-time
Posted 15 days ago
Job description
Job Summary:
Blue Cross Blue Shield Association is seeking a Senior Director for Data Science and Gen AI to lead the development and application of Generative AI and advanced machine learning capabilities. This role involves setting the technical direction for AI initiatives, managing data science teams, and collaborating across the organization to drive innovation and implement advanced analytics in healthcare data.
Responsibilities:
• Responsible for setting the enterprise technical and analytic strategy for Generative AI for BCBSA’s BSI and national data assets, including long-term vision, architectural direction, capability roadmap, and standards for scalable, responsible AI embedded across all products.
• Serve as a trusted advisor to executive leadership, with accountability for key technical and analytic decisions, translating complex models and analytic findings into actionable insights that inform and activate business strategies.
• Lead and individually contribute to large-scale data science initiatives, including end-to-end machine learning and GenAI model development, experimentation, and implementation.
• Act as the subject matter expert in computational algorithms, model evaluation, and advanced data interpretation to assess performance, tradeoffs, and impact.
• Lead and manage data science and machine learning R&D efforts across multiple product lines, data domains (medical, pharmacy, emerging clinical data), and customer-facing platforms.
• Partner with Product Strategy to identify and apply Generative AI and advanced analytics within the product development process, with a focus on emerging healthcare trends and priorities.
• Collaborate closely with Data Engineering to design scalable applications and optimal data architecture leveraging structured and unstructured data.
• Establish and govern enterprise standards and best practices for analysis plans, ensuring rigor, reproducibility, ethical AI use, and compliance with regulatory and security requirements.
• Drive education and adoption of data science and Generative AI across the organization by communicating vision, use cases, and value.
• Manage and develop senior data science talent, supporting professional growth and succession readiness.
• Manage external analytics vendors and partnerships, including relationships with AI vendors and academic experts in LLMs and NLP.
• Work with executive leadership and cross-functional stakeholders to define requirements and develop AI and analytics R&D and strategic roadmaps.
• Evaluate and implement new AI, ML, and Generative AI tools and technologies to enhance organizational capability and competitiveness.
• Oversee the development of training datasets, data preprocessing pipelines, and testing frameworks to support advanced analytics and AI solutions.
Qualifications:
Required:
• Master's Degree Focused on machine learning (ML) or adjacent fields, including Analytics, Data Science, Statistics, Mathematics, Computer Science, or a related field
• At least 15 years experience with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects.
• Experience with streaming and near-real-time data in healthcare (such as HL7 streams or FHIR applications) industry.
• Experience with establishing and governing a Machine Learning Operationalization (MLOps) program, including the use of MLOps tools (e.g., MLFlow, Kubeflow).
• Experience with major cloud computing platforms, AWS experience is highly preferred.
• Experience with cloud-based data-as-a-service platforms (e.g., Snowflake, Synapse, Databricks).
• Experience with Agile development practices, including development frameworks (e.g., Scrum or Kanban) and tools for continuous integration and deployment (CI/CD).
• Experience working with Generative AI (GenAI), Large Language Models (LLM), Natural Language Processing (NLP), and other advanced analytics.
• Strong fundamental knowledge of probability theory, stochastic systems, Bayesian inference, predictive modeling, supervised/unsupervised/deep learning Natural language processing experience, particularly in the biological and medical domains.
• A record of successful formulation, approval, and implementation of organizational strategies around advanced analytics in AI/ML.
• Expertise in using machine learning and analytic tools such as SQL, R, and/or Python to analyze data in applied professional projects.
• Familiarity with relational databases (e.g., MS SQL, Oracle, Postgres, MySQL).
• Expertise in visualizing and manipulating big data sets.
• Strong verbal and written communications skills with the demonstrated ability to explain complex technical concepts to a lay audience.
• Demonstrated ability to deliver successful, profitable, repeatable, referenced analytic solutions.
• Proven ability to develop staff to deliver world-class analytic solutions.
• Knowledgeable in complex modeling topics, advanced statistics/biostatistics, algorithm design, and ML software packages.
Preferred:
• Experience with major cloud computing platforms, AWS experience is highly preferred.
Company:
Blue Cross Blue Shield Association is a national federation of 36 independent operated Blue Cross and Blue Shield companies. Founded in 1929, the company is headquartered in Chicago, USA, with a team of 1001-5000 employees. The company is currently Late Stage.
Blue Cross Blue Shield Association is seeking a Senior Director for Data Science and Gen AI to lead the development and application of Generative AI and advanced machine learning capabilities. This role involves setting the technical direction for AI initiatives, managing data science teams, and collaborating across the organization to drive innovation and implement advanced analytics in healthcare data.
Responsibilities:
• Responsible for setting the enterprise technical and analytic strategy for Generative AI for BCBSA’s BSI and national data assets, including long-term vision, architectural direction, capability roadmap, and standards for scalable, responsible AI embedded across all products.
• Serve as a trusted advisor to executive leadership, with accountability for key technical and analytic decisions, translating complex models and analytic findings into actionable insights that inform and activate business strategies.
• Lead and individually contribute to large-scale data science initiatives, including end-to-end machine learning and GenAI model development, experimentation, and implementation.
• Act as the subject matter expert in computational algorithms, model evaluation, and advanced data interpretation to assess performance, tradeoffs, and impact.
• Lead and manage data science and machine learning R&D efforts across multiple product lines, data domains (medical, pharmacy, emerging clinical data), and customer-facing platforms.
• Partner with Product Strategy to identify and apply Generative AI and advanced analytics within the product development process, with a focus on emerging healthcare trends and priorities.
• Collaborate closely with Data Engineering to design scalable applications and optimal data architecture leveraging structured and unstructured data.
• Establish and govern enterprise standards and best practices for analysis plans, ensuring rigor, reproducibility, ethical AI use, and compliance with regulatory and security requirements.
• Drive education and adoption of data science and Generative AI across the organization by communicating vision, use cases, and value.
• Manage and develop senior data science talent, supporting professional growth and succession readiness.
• Manage external analytics vendors and partnerships, including relationships with AI vendors and academic experts in LLMs and NLP.
• Work with executive leadership and cross-functional stakeholders to define requirements and develop AI and analytics R&D and strategic roadmaps.
• Evaluate and implement new AI, ML, and Generative AI tools and technologies to enhance organizational capability and competitiveness.
• Oversee the development of training datasets, data preprocessing pipelines, and testing frameworks to support advanced analytics and AI solutions.
Qualifications:
Required:
• Master's Degree Focused on machine learning (ML) or adjacent fields, including Analytics, Data Science, Statistics, Mathematics, Computer Science, or a related field
• At least 15 years experience with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects.
• Experience with streaming and near-real-time data in healthcare (such as HL7 streams or FHIR applications) industry.
• Experience with establishing and governing a Machine Learning Operationalization (MLOps) program, including the use of MLOps tools (e.g., MLFlow, Kubeflow).
• Experience with major cloud computing platforms, AWS experience is highly preferred.
• Experience with cloud-based data-as-a-service platforms (e.g., Snowflake, Synapse, Databricks).
• Experience with Agile development practices, including development frameworks (e.g., Scrum or Kanban) and tools for continuous integration and deployment (CI/CD).
• Experience working with Generative AI (GenAI), Large Language Models (LLM), Natural Language Processing (NLP), and other advanced analytics.
• Strong fundamental knowledge of probability theory, stochastic systems, Bayesian inference, predictive modeling, supervised/unsupervised/deep learning Natural language processing experience, particularly in the biological and medical domains.
• A record of successful formulation, approval, and implementation of organizational strategies around advanced analytics in AI/ML.
• Expertise in using machine learning and analytic tools such as SQL, R, and/or Python to analyze data in applied professional projects.
• Familiarity with relational databases (e.g., MS SQL, Oracle, Postgres, MySQL).
• Expertise in visualizing and manipulating big data sets.
• Strong verbal and written communications skills with the demonstrated ability to explain complex technical concepts to a lay audience.
• Demonstrated ability to deliver successful, profitable, repeatable, referenced analytic solutions.
• Proven ability to develop staff to deliver world-class analytic solutions.
• Knowledgeable in complex modeling topics, advanced statistics/biostatistics, algorithm design, and ML software packages.
Preferred:
• Experience with major cloud computing platforms, AWS experience is highly preferred.
Company:
Blue Cross Blue Shield Association is a national federation of 36 independent operated Blue Cross and Blue Shield companies. Founded in 1929, the company is headquartered in Chicago, USA, with a team of 1001-5000 employees. The company is currently Late Stage.
About Blue Cross Blue Shield Association
Sourced by ZipRecruiter
Industry
Health care and social assistance
Company size
1,001 - 5,000 Employees
Headquarters location
Augusta, GA, US
Year founded
1910