Work with a variety of large datasets including pharmacy and medical claims transactions, member information, voice call transcripts, survey data, web log data
Requirements
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
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
Previous work experience in software engineering a plus
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
Experience with Microsoft Office Suite
Benefits
Project-based experience
Executive speaker series
Volunteer events
Career development workshops
Networking opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningdata pipelinesSQLPythonScikit LearnMLlibTensorFlowPyTorchApache SparkBig Data