Data Scientist - Mid level - Military veterans preferred

Description

As part of the Strategy, Growth, and Innovation (SGI) organization, SAIC is seeking support for our horizontal Artificial Intelligence (AI) business.  The AI team focuses on developing and selling new analytic solutions that assist our customers in their mission effectiveness.  The team maintains leadership on emerging concepts and encourages innovation.  We are looking to hire a variety of individuals who have multiple years of experience in data science, and who have demonstrated experience in several of the following areas: predictive analytics,  AI/ML, Data Ops, synthetic data creation, Natural Language Processing, Computer Vision, Quantum computing, High Performance Computing, deep learning, and/or Robotic Process Automation.  Preference will be given to candidates who have experience in white paper and proposal writing.  This position can be worked remotely from anywhere within the U.S. 

Qualifications

• Minimum five (5) years of experience related to data science and the manipulation of large data sources. 
• Demonstrated ability to write for proposal, RFI and White Papers
• Demonstrated expertise in the data analytics field, building analytic models and methods, and the skillsets to be able to provide end-to-end technical solution. 
• Ability and experience assessing business objectives, conducting gap analysis of existing versus needed capability, and identifying business requirements.
• Experience developing potential technical solutions to meet business needs and support analysis of alternatives for best fit.
• Experience evaluating technical trends and provide recommendations for technology and architecture to meet business objectives.

Education Required:

Bachelors and five (5) years or more of related experience; Masters and three (3) years or more related experience.

Clearance: 

No clearance required.

 

Target salary range: $105,001 - $115,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.