The Cigna Group's Evernorth Health Services division is seeking interns to apply Advanced Analytics and Data Science to Healthcare's biggest challenges, aiming to improve health and increase vitality through innovative solutions for prediction, prevention, and treatment of disease.
Requirements
- Ability to work with a variety of data sources with SQL & Python
- Experience with Python Machine Learning (ML) Libraries (Scikit Learn, MLlib, TensorFlow, and PyTorch)
- Exposure to AWS cloud services and running Apache Spark applications
- Experience with API development leveraging Fast API / Flask
- Developing and deploying Spark/Databricks jobs with enterprise tool stacks like Jenkins / GitHub Actions
- Deployment utilizing containerization solutions like Docker and Kubernetes
- Experience working in distributed computing and Big Data Technologies like Hive, Spark, Scala, HDFS
Responsibilities
- build and deploy machine learning frameworks
- accelerating development to deployment timelines
- supporting data scientists in their projects
- creating scalable algorithms
- developing efficient data pipelines
- Point of Concept (POC) for building an embedding store leveraging autoencoders
- Build frameworks to fast-track model development to deployment lifecycles
Other
- Working towards a Master’s Degree or PhD in quantitative disciplines such as Statistics, Applied Mathematics, Computer Science, Econometrics, Finance, Engineering, Operations Research, Bioinformatics, Information Systems, Computational Linguistics or related quantitative disciplines or other similar degree
- Previous work experience in software engineering a plus
- Experience with Microsoft Office Suite
- If you will be working at home occasionally or permanently, the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 10Mbps download/5Mbps upload.
- 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.
