Data Scientist (TS/SCI with Full Scope Poly required) – 1691
Fort Meade, MD
Data Scientist (TS/SCI with Full Scope Poly required) – 1691
Location: Fort Meade, MD - Onsite Relocation assistance: No – sign on bonus possible to offset the costs. Visa sponsorship eligibility: No
** Skills:TS/SCI with Poly, Data Scientist, R, Python, SAS, or MATLAB, Machine Learning **
Position Responsibilities: A data scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.
Required Degree and Experience:
Bachelor's degree in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science) + 7 years of experience, Masters Degree + 5 years of experience, or PhD + 2 years of experience
Must have:
Bachelor Degree in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science) + 7 years of experience, Masters Degree + 5 years of experience, or PhD + 2 years of experience
Active TS/SCI security clearance with the full scope Polygraph required
Programming experience with data analysis software such as R, Python, SAS, or MATLAB.
Developed experiments to collect data or models to simulate data when required data are unavailable.
Developed feature vectors for input into machine learning algorithms.
Identified the most appropriate algorithm for a given dataset and tune input and model parameters.
Evaluated and validated the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices).
Overseen the development of individual analytic efforts and guide team in analytic development process.
Guide analytic development toward solutions that can scale to large datasets.
Partner with software engineers and cloud developers to develop production analytics.
Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation.