Senior Data Scientist

Overview

The Senior Data Scientist will support our customers initiatives by developing/maintaining/analyzing data sets in order to create models and determinate potential outcomes. The position is immediately available for qualified candidates with the appropriate clearance.

Responsibilities

The Senior Data Science Analyst shall be able to demonstrate experience and expertise in the following:

• Programming languages such as Python(inclusive of libraries that are used in data science e.g. numpty, pandas, and scipy); R; Julia (dynamic programming language), or other programming languages.
• The development of frameworks for creating and integrating machine learning models such as TensorFlow, Pytorch, Jupyter Notebook and or Apache Hadoop
• The development and use of Visualizatin Tools to create interactive scientific graphing capabilities. These capabilities and experience can be a combination of tool familiarity exhibited with competency in Plotly, Tableau, PowerBI, Qlik, and/or Google Charts
• Understanding of relevant statistical measures, development and evaluation of data sets.
• Salary Range: $130,000 - $160,000/Year, DOE

Skills Required

The Senior Data Science Analyst shall apply the principles, theories and analytical methods of Data Science Analysis, which encompasses the following:

• Tool and method development by using high-level modeling, machine learning techniques, and software languages
• Hypothesis development and validation of budget and schedule sufficiency/achievability and risk parameters
• Working with data visualization tools and creating data visualization concepts
• Experience developing queries and reports, parsing and merging data from complex datasets
• Establishing and integrating large datasets, data entry , data conditioning and cleaning, data mining and end-to-end database management
• Developing customer-facing reporting tools to provide timely and accurate decision-support and information
• Understanding of how data science enables cost estimating, IPM and cross program analysis for comprehensive, data driven methods and assessments.

Education

Bachelor's degree required, preferably in math, engineering, business, or the sciences.