Position Responsibilities:
A data scientist will develop machine learning data mining statistical and graphbased 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 datadriven 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:
Bachelors 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
Required Skills:
- Programming experience with data analysis software such as R Python SAS or MATLAB.
- Develop experiments to collect data or models to simulate data when required data are unavailable.
- Develop feature vectors for input into machine learning algorithms.
- Identify the most appropriate algorithm for a given dataset and tune input and model parameters.
- Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation ROC curves confusion matrices).
- Oversee 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.
confusion matrices,automation,sas,algorithms,model evaluation,feature engineering,graph-based algorithms,python,matlab,data visualization,statistical analysis,data,data analysis,operations research,cross validation,algorithm development,research,metrics,quantative analysis,r,machine learning,active ts/sci clearance,government,datasets,analytics,statistics,data mining,roc curves,diverse groups