Website Expert In Recruitment Solutions
Expert In Recruitment Solutions
Company : Expert In Recruitment Solutions
Data Scientist
(active TS/SCI with Full Scope Poly Clearance required)
Location: Fort Mead, MD – Onsite
Relocation: Not offered but a sign on bonus can help offset moving expenses
Full-time employment
Job Summary
Providing analytic solutions to hundreds of companies across numerous industries, with exposure to a wide range of techniques and tools.
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
PhD + 2 years of experience
Must have:
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 is 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.