Computational Data Scientist

Position Summary

SURVICE Engineering is currently seeking a Computational Data Scientist to support our Aberdeen Research Operation. You will accelerate your career and become an integral team member within the defense community.

Primary Duties And Responsibilities

• Carry out forward-looking programs of materials research and process modeling leveraging data science methodologies and tools including artificial intelligence, machine learning (ML), probabilistic graph models, neural networks, or other emergent techniques.
• Work with a multidisciplinary team of ARL experimental, theoretical, and computational scientists through decision making aids such as visual analytics and human-in-the-loop strategies to improve scientific efficiency and impact.
• Apply learning algorithms on high-dimensional, complex and/or streaming data sets with limited labels and of diverse quality for smart decision making.
• Pursue data processing of heterogeneous types from numeric, digital objects, images, structured to unstructured from data capture, data integration, data cleaning to data management.
• Interface with data scientists in academic, industrial and government labs to identify and transition cutting edge tools for use at ARL, and work with outside partners to fill critical gaps in skills and capabilities.
• Prepare presentations and written documents summarizing efforts in Government format.

Minimum Qualifications

• Masters of Science or PhD in Computer Science or Math related discipline and 3+ years of relevant experience.
• Exceptional candidates with less experience will be considered.
• Candidates are not required to possess all qualifications; if you possess some of the desired qualifications, please apply.
• MS or PhD concentration in machine learning with at least three (3) independent projects including internships and thesis work OR minimum of five (5) years of dedicated experience with machine learning.
• Practical experience in applying data science to model complex real-world problems.
• Proficient in using Python and AI/ML models.
• Experience in communicating results through reports and presentations.