Data Scientist - Ontology

SRC, Inc., a not-for-profit research and development company, combines information, science, technology and ingenuity across our family of companies to deliver innovative, advanced defense solutions and products that are redefining possible^®. Since 1957, our commitment to the customer and the best solution – not the bottom line – has remained a core value that guides our efforts. This passion for quality carries through to the technologies we invent and manufacture, the laboratories and facilities we build, the people we hire, and the communities we support.

At SRC, we provide you the freedom and the resources to solve “impossible” problems in a collaborative work environment that integrates research, development and manufacturing. We strive to proactively identify and eliminate barriers that prevent our employees’ full participation and are committed to ensuring an inclusive and equitable workplace for all our employees. When you join our team, you’ll be a part of something truly meaningful. You’ll join more than 1,300 engineers, scientists and professionals — with 20 percent of those employees having served in the military — helping to keep America and its allies safe and strong.

In return, you’ll enjoy an inclusive work environment, receive a competitive salary, and experience a comprehensive benefits package that includes four or more weeks of paid time off to start, 10 percent of an employee’s compensation contributed toward retirement, and 100 percent tuition support.

SRC, Inc. is currently seeking a Data Scientist, with Ontology focus, for an exciting opportunity in our Electronic Warfare & Services Division.  The selected candidate will contribute to the assessment of scientific and technical (S&T) capabilities of current and future foreign Advanced Conventional Weapons systems; to forecast and predict future capabilities and battlefield effectiveness; and to create high-fidelity models and simulations of such systems.

Responsibilities:

• Provide support in developing and application of data mining analysis, aggregation, fusion, and visualization to process, analyze, and integrate raw data facilitating the production and dissemination of intelligence relating to foreign ground forces research, development, systems, weapon employment, effects, and operations
• Perform data analysis, including manipulating datasets and interpreting findings using a mix of programs/environments (such as R, Python, MATLAB) and techniques
• Conducts multidisciplinary research and collaborates with equipment designers and/or hardware engineers in the planning, design, development, and utilization of electronic data
• Integrate statistical data analysis with geospatial data and services to produce web services in an interactive map application
• Contribute to data-driven all-source analysis, assessment, and decision making for developing combat ready realistic foundational intelligence in support of TMAP and ITASE
• Integrate and analyze data as necessary using MATLAB, Python, R, and C , and conduct statistical analysis of geospatial and S&T data
• Process, tag/label/parse/index unstructured, semi-structured, and structured classified and unclassified data sets

Position Requirements:

• Education: Bachelor’s in Science degree
• Experience: 3 years of related experience in information science, computer science, engineering, library science, ontology, semantics
• Experience developing data transformation pipelines to combine data from multiple sources with ontological models to create knowledge graphs
• Experience with the following software languages and tools is a plus:
  • C , Java, Python, Git, JIRA, MATLAB/Simlink, and CAD tools
• Familiarity with Big Data (parallel processing power and options for handling analysis of data)
• Working understanding of ontology engineering (Familiarity with MarkLogic, OWL, Protege, Cyc, Cypher, or similar)
• Familiarity with TMAP/ITASE and other intelligence community databases a plus (e.g. SPIRIT)
• Ability to work in a fast-paced environment, think independently, and overcome technical challenges
• Ability and desire to work on multi-disciplinary engineering teams
• Excellent verbal/written communication skills
• Excellent problem solving skills