Logo
Penn Foster

Jr. Data Scientist

Penn Foster, Newport News, Virginia, United States, 23600


Job Description:

Summary:Yorktown Systems Group, Inc. is seeking a qualified Jr. Data Scientist to provide professional services and support to the TRADOC Deputy Chief of Staff for Intelligence (G-2) Operational Environment (OE) and Core Functions. The TRADOC G-2 facilitates and acts as the principal enabler for continuous learning across all TRADOC lines of effort through acquiring, analyzing, creating, organizing, applying and transferring data, information, and knowledge in the context of current and future operations. The G-2 is responsible for delivering the Operating Environment to facilitate the training of deploying units on joint, national and interagency information, emerging asymmetric capabilities gleaned from world-wide operations; integrating processes, practices, concepts and materiel capabilities into Joint and Service DOTMLPF solutions; and coordinating with the training centers to provide realistic enemy and environmental signatures into models and simulations in support of realistic training.Specific duties may include, but are not limited to:Work alongside a team of Data Scientists, Data Engineers, Developers and Subject matter experts creating solutions which utilize a variety of data mining/data analysis methods and data tools to build and implement models using creative algorithms, graphics, and dashboards to provide an accurate representation of the client’s data.Work with Government stakeholders to identify opportunities for leveraging data to drive data driven decision making.Mine and analyze data from existing databases to drive decision making.Assess the effectiveness and accuracy of new data sources and data gathering techniques.Develop custom data models and algorithms to apply to data sets.Use predictive modeling.Coordinate with different functional teams to implement models and monitor outcomes.Develop processes and tools to monitor and analyze model performance and data accuracy.Job Requirements:Required Qualifications:1-2 years of experience in analytics, manipulating data sets, and building statistical models.Experience using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets.Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.Experience querying databases and using statistical computer languages: R, Python, etc.Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.Experience with distributed data/computing tools.Experience visualizing/presenting data for stakeholders.Strong problem-solving skills.Experience working with and creating data architectures.Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.Excellent written and verbal communication skills for coordinating across teams.A drive to learn and master new technologies and techniques.Excellent organizational skills.Ability to obtain a SECRET clearance is required.Due to the nature of the government contract requirements and/or clearance requirements, US citizenship is required.Desired Qualifications:Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.Development in cloud-based computing platforms, especially capable of SaaS development in the Microsoft Azure environment.Experience utilizing repos, pipelines, and test plans in Azure DevOps.Previous military/deployment or exercise support experience a plus.Clearance:

Ability to obtain a SECRET clearance.Location:

Fort Eustis, VATravel:

Some travel may be required.

#J-18808-Ljbffr