Join Our World-Class Team at QinetiQ US as a Data Scientist

Company Overview

At QinetiQ US, we are a premier team of professionals leading the way in next-generation technology and products across robotic and autonomous platforms, ground, soldier, and maritime systems in over 50 locations globally. Our innovative work spans across sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR).

Our dedicated experts in defense, aerospace, security, and related fields collaborate to discover new methods of protecting the American Warfighter, Security Forces, and Allies. Joining QinetiQ US means playing a crucial role in the safety and security of the world around us. Partnering with our customers, we save lives, reduce societal risks, and maintain the global infrastructure on which we all rely.

Why Join QinetiQ US?

Are you ready to tackle a variety of complex challenges? At QinetiQ US, you’ll experience a unique working environment where innovative teams blend diverse perspectives, disciplines, and technologies to solve intricate problems. In our inclusive environment, you can be yourself, feel valued, and achieve your full potential. We provide workplace flexibility, support your health and well-being, and offer opportunities to work with purpose. We are dedicated to your success, both professionally and personally.

Position Overview

QinetiQ US is seeking a results-driven Senior Data Scientist to support NSG strategies through the development of automated collection models, dynamic analytic models, and workflow automations.

Responsibilities

• Create automated collection models, dynamic analytic models, and workflow automations as per NSG strategies.
• Enhance operational performance through performance data evaluation, customer interaction, and standardized maintenance cycles.
• Apply data science and visual programming to support and streamline analysis tasks identified by stakeholders and the government.
• Enhance technical solutions for IC intelligence integration, automated collections, tipping and cueing, information sharing, and visualization.
• Conduct extensive data collections and analytic modeling, as well as data processing, data mining, and visualization.
• Perform gap analysis on existing technologies and processes, keeping customers informed on project progress and emerging technologies.
• Communicate data-driven findings and automation to both technical and non-technical audiences.
• Design, integrate, and maintain Bayesian Belief Network (BBN) processes with automation tools or scripts for predictive, activity-based automated collection.
• Address processing issues, identify permanent solutions, and close technology gaps through customer elicitation.
• Train and integrate new tools, processes, and capabilities used in collection orchestration, providing support for emerging requirements as assigned by the government.

Required Qualifications

• Active TS/SCI Clearance. #qinetiqclearedjob
• Proficiency in geospatial software applications and tools, such as visual programming (JEMA, FADE/MIST, ECO/ETAS), Python, SQL, Git, GIMS, AWS Sagemaker, AWS Cloud, ESRI ArcGIS, statistics (descriptive, Bayesian), Markov-Chain modeling, TensorFlow, Linear Algebra, R, SAS, NLP.
• 5+ years of relevant experience with a bachelor's degree (or a combination of years of experience and professional certifications/trainings in lieu of a degree).

Company EEO Statement

QinetiQ US is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive equal consideration for employment without regard to race, age, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran status.

Accessibility/Accommodation

If you require a reasonable accommodation due to a medical condition or disability for any part of the employment process, please email or call (540) 658-2720 Opt. 4. Please state the nature of your request and provide your contact information.

Company Name: QinetiQ US

Job Title: Senior Data Scientist