The Cigna Group is looking to solve the problem of developing and operationalizing transformer based deep learning models trained on health insurance data sources to support high-value enterprise-wide initiatives.
Requirements
Strong proficiency in Machine Learning and Statistical Methodology and Practices
Strong proficiency in Python, SQL and version control (e.g., Git)
Theoretical and practical deep learning expertise building and deploying deep learning models in an enterprise environment
Proficiency with TensorFlow and/or PyTorch
Thorough understanding of ML lifecycle, including necessary tradeoffs and associated risks
Ability to promote best coding practices, championing a culture of documentation
Health care data (e.g., claims, EHR) knowledge preferred
Responsibilities
Support high-value enterprise Data Science initiatives
Act as a subject matter expert (SME) in the area of deep learning
Creates data science specific project goals associated with project deliverables
Develop and maintain strong collaborative relationships with technical and business matrix partners
Independently delivers clear and well-developed presentations for both technical and business audiences
Mentor and champion junior Data Science team members via established development programs and on a project-by-project basis
Own a project end-to-end e.g., scoping, business value estimation, ideation, dev, prod, timeline
Other
Ability to work and influence cross functionally with technical and non-technical partners to implement solutions with measurable value
Bachelor's degree or higher (not explicitly mentioned but implied)
Must have a cable broadband or fiber optic internet service provider with speeds of at least 10Mbps download/5Mbps upload for remote work
Must be eligible to work in the United States (implied)
Qualified applicants will be considered without regard to race, color, age, disability, sex, childbirth (including pregnancy) or related medical conditions including but not limited to lactation, sexual orientation, gender identity or expression, veteran or military status, religion, national origin, ancestry, marital or familial status, genetic information, status with regard to public assistance, citizenship status or any other characteristic protected by applicable equal employment opportunity laws
