Posted today
Top Secret/SCI
Unspecified
Unspecified
IT - Data Science
Annapolis, MD (On-Site/Office)
What You'll be Owning:
What You Must Have :
What Would Be Nice to Have:
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- 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.
What You Must Have :
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- Bachelor's from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science).
- Five years of experience analyzing datasets and developing analytics, five years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
- An additional two years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Master's degree.
- A PhD from an accredited college or university in a quantitative discipline can be substituted for three years of experience.
- Active TS/SCI w/ poly
What Would Be Nice to Have:
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- Produce data visualizations that provide insight into dataset structure and meaning
- Work with subject matters experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs)
- Incorporate SME input into feature vectors suitable for analytic development and testing
- Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes
- Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics
- Develop statistical tests to make data-driven recommendations and decisions
- 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
- Make recommendations for analytic development toward solutions that can scale to large datasets
- Collaborate with software engineers, cloud developers, and appropriate stakeholders to develop production analytics
- Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation
group id: 90883154
