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Data Scientist

Job ID: 2312170
Location: REMOTE WORK, AL, United States
Date Posted: Sep 5, 2023
Category: Information Technology
Subcategory: Data Scientist
Schedule: Full-time
Shift: Day Job
Travel: Yes, 10 % of the Time
Minimum Clearance Required: Secret
Clearance Level Must Be Able to Obtain: None
Potential for Remote Work: Remote
Benefits: Click here

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Job Description

Description

SAIC is seeking a forward-thinking Data Scientist to join an integrated team in conducting research and analysis to support a series of Training System Requirements Analyses (TSRA) for the US Air Force Agency for Modeling and Simulation (AFAMS) program supporting the Mobility Air Force (MAF).

(This is a fully remote position, with no onsite requirement)

Impact: Analysis and recommendations have the opportunity to shape the future of MAF aircrew training.

About this position:

As a Data Scientist, you will work in cross-functional teams with data at all stages of the analysis lifecycle to derive actionable insight. You will play a strategic and technical role in organizational research for the MAF through targeted use of analytics as well as in the pre-analytics areas of data collection, cleaning, storage and retrieval. In this role, you will follow a scientific approach to generate value from data while leveraging statistical programming languages and data visualization to achieve this goal.

At SAIC we apply actionable analytics that combine human ingenuity and machine power to produce insights often in the blink of an eye. Our advanced analytics serve to support our customers’ decision-making and strategic planning across multiple domains and disciplines. Through our innovative, effective and efficient solutions we ensure our customers have the edge they need to ensure mission success.

 

Qualifications

Required Education, Experience, Skills, & Attributes:

  • Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience; or relevant years of experience in lieu of degree.

  • Experience applying methods of data science and data visualization (e.g. through Excel, Python, R, etc.).
  • US Citizen and possess an active Secret Clearance

Desired Experience, Skills, & Attributes:

  • Master's degree in Statistics, Data Science, Mathematics, Operations Research or a related quantitative field
  • Working knowledge of current academic, industry, and/or Air Force training techniques and technologies.
  • Familiarity with US government network environments and policies.
  • Experience with experimental design and supervised/unsupervised machine learning approaches in using programming languages to automate tasks


Target salary range: $100,001 - $125,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

Covid Policy: SAIC does not require COVID-19 vaccinations or boosters. Customer site vaccination requirements must be followed when work is performed at a customer site.

Overview

SAIC® is a premier Fortune 500® technology integrator driving our nation's technology transformation. Our robust portfolio of offerings across the defense, space, civilian, and intelligence markets includes secure high-end solutions in engineering, digital, artificial intelligence and mission solutions. Using our expertise and understanding of existing and emerging technologies, we integrate the best components from our own portfolio and our partner ecosystem to deliver innovative, effective and efficient solutions that are critical to achieving our customers' missions.

We are approximately 24,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer, fostering a culture of diversity, equity, and inclusion, which is core to our values and important to attract and retain exceptional talent. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $6.9 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.

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