Terms of Employment

• Contract, 12 Months (Extension Highly Likely)
• This position is remote. Once or twice per quarter, this individual should be willing to travel to the Washington, DC / Northern Virginia area for moments that matter meetings.

Overview

The initial focus for this Data Scientist will be to support an organizational migration project moving from on-premises to the cloud specifically AWS. The Data Scientist will be responsible for deploying data models in the cloud. Once the migration is complete, the Data Scientist will be responsible for building and deploying more and more data models as business dictates.
Required Skills & Experience

• Possesses a Bachelor s or Masters degree with the ability to transform concepts into practical solutions
• 8 years of experience in data science
• Proficiency in Python
• Proficiency in SQL and/or HiveQL
• Experience working in AWS leveraging SageMaker with knowledge enough to build and deploy data models in a cloud environment (deployment scripts are in Python)
• Experience successfully implementing Machine Learning (ML) solutions with knowledge of machine learning methods like k-nearest neighbors, random forests, ensemble methods, and more
• Proficiency in data science modeling such as Deep Learning, Decision Trees, Random Forest, Neural Networks, Supervised/Unsupervised Learning, Forecasting, Predictive Modeling and Clustering
• Experience leading large data science and/or machine learning projects
• Comfortable presenting abstract concepts to different audiences
• Ability to write production-ready code including documentation and unit tests
• Deep knowledge of fundamentals of data mining and statistical predictive modeling, and extensive experience applying these methods to real world problems
• Ability to initiate and drive projects to completion with minimal guidance
• Ability to communicate the results of analyses in a clear and effective manner

Preferred Skills & Experience

• Understanding of Agile methodologies
• PySpark experience.
• Proficiency in Spark/Scala for classical statistical analysis and data modeling
• Experience engineering large language models / generative AI tools
• Experience with statistical packages such as R, MATLAB, SPSS, SAS, Stata, etc.
• Experience with data science/ML techniques as applied to healthcare, specifically experience on recommendation engines for members and claims anomaly detection
• Proficiency with healthcare analytics and data structures
• Experience with large data sets and distributed computing (Hive/Hadoop)