What are the responsibilities and job description for the Data Scientist Defense &Areospace position at SpeakEZ Virtual Solutions LLC?
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
Required Skills
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
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.
