Governance - Data Science And AI/ML

The Governance, Data Science and AI/ML practitioner will identify, implement, and deliver accurate and quality analyses that translate data in sound organizational decisions.

Objectives
defining and operationalizing an Enterprise Model Governance framework to support the production and maintenance of advanced analytic models at BCBS NC. Additionally, this resource will work with data scientists to define and develop model metadata and monitoring RESTful API endpoint which enables integration with internal or external governance solutions.

Resource will also produce Governance Model to dynamically assess systems/assets and analytic proficiency, relevancy, and accuracy.

Partnership with Principal Analytics Governance Engineer, Data Governance, and AI/ML teams to help define application strategy across key governance tools is required.

Independently:

• Define and operationalize an Enterprise Model Governance framework to support the production and maintenance of advanced analytic models at BCBS NC
• Partner with data scientists to define and develop model metadata and monitoring RESTful API endpoint which enables integration with internal or external governance solutions
• Produce Governance Model to dynamically assess systems/assets and analytic proficiency, relevancy, and accuracy
• Collaborate with Principal Analytics Governance Engineer, Data Governance, and AI/ML teams to define application strategy across key governance tools
• Own delivery of large and/or complex governance and engineering projects
• Lead in the development and testing of hypotheses across all functional data sets
• Lead requirements gathering sessions with business and technical staff to distill technical requirement from business requests
• Define and implement integrated data models, allowing integration of data from multiple sources
• Design and develop scalable, efficient data pipeline processes to handle data ingestion, cleansing, transformation, integration, and validation
• Define and implement data stores based on system requirements and consumer requirements
• Design and develop models to understand and solve complex business solutions using a variety of methods including data mining, statistical analysis, predictive modeling and analysis, stochastic modeling, pattern recognition, probability analysis, and network analysis
• Design and implement production models leveraging technologies such as SAS, Python, and R
• Leverage existing data sets and engineer new data sets including development of SQL queries, data integration and resolution of data quality issues
• Apply advanced conceptual understanding of Big Data systems to data set engineering and analytic model implementation
• Lead reviews of analytic models and algorithms
• Identify actionable insights, suggest recommendations, and influence business direction by effectively communicating results to cross functional groups
• Document and test analytic processes including performance and thorough data validation and verification

Hiring Requirements

• Master's Degree in Data Science, Applied Mathematics, Computer science, Statistics, Biostatistics, Epidemiology, Health Services Research, or a field closely related to Data Science specialization, or equivalent combination of transferrable experience and education
• 5 years of the following with increasing scope of project responsibilities:
  • SQL programming (Advance SQL programming)
  • Demonstrated experience with design and implementation of analytic models and methodologies for new applications
  • Extensive experience in using Python, R or other programming language for data science projects
  • Advanced experience working with large and complex data sets to develop regression and classification models.
• Deep knowledge of state-of-the art techniques in machine learning, statistics, optimization or related fields Demonstrated experience in successfully delivering data science projects.