Lead Data Scientist - Reston, United States - Ntech Workforce

Description

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 Bachelors 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)

by Jobble

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