Responsible for the management and growth of the Responsible AI Data Analyst.
Responsible for understanding challenges/problems within the healthcare industry, specifically related to the ethical development and use of AI.
Lead technical project discussions as the representative from the Responsible AI team.
Collaborate with data scientists, ML engineers, Cloud engineers, and other IT professionals to integrate responsible AI practices in the MLOPs workflow.
Assist with No Code and Low Code AI proof of concept initiatives by collaborating with stakeholders, ITG partners, and the RAI Product Manager.
Support the implementation of No Code and Low Code AI use cases and products by championing Responsible AI best practices & guidelines by building prototypes and demos.
Assist in building workflow for tracking and analyzing AI products and opportunities, in addition to presenting analytics.
Support requests from the product and data science teams.
Lead the design and implementation of the monitoring of product function and performance.
Contributes to improving department processes and standards.
Design and build analytics in spreadsheets, dashboards, and/or advanced scripting tools with sound statistical methods to answer business, operations, clinical, financial, and other domain questions.
Requirements & Skills:
Bachelor’s degree – Required
Master’s degree – Preferred
5+ years of experience in analytics development or equivalent experience with data, decks, and dashboards in at least one major business domain, who understands basic statistics concepts and is looking for continued analytics growth and professional opportunity. – Required
5+ years of experience in Python, SQL, ETLs, Teradata, Pipelines, and Power BI – Required
5+ years of experience in Microsoft Azure or Google Cloud Platform. – Required
3+ years of experience in leading a technical team or project delivery in the data space. – Required
Technology generalist in both emerging and legacy stacks. – Preferred
Hands-on experience with development/API integration to quickly build prototypes and demos. – Preferred
Familiarity with data governance and model lifecycle management. – Preferred
Experience with third party vendor management and build/buy/partner trade-offs. – Preferred
Experience implementing governance frameworks, policies, and best practices in a large-scale environment. – Preferred
Google Cloud Certification and Microsoft Azure Certification preferred. – Preferred
