Responsibilities

Involved in the analysis of unstructured and semi-structured data, including latent semantic indexing (LSI), entity identification and tagging, complex event processing (CEP), and the application of analysis algorithms on distributed, clustered, and cloud-based high-performance infrastructures. Exercises creativity in applying non-traditional approaches to large-scale analysis of unstructured data in support of high-value use cases visualized through multi-dimensional interfaces. Handle processing and index requests against high-volume collections of data and high-velocity data streams. Has the ability to make discoveries in the world of big data. Requires strong technical and computational skills - engineering, physics, mathematics, coupled with the ability to code design, develop, and deploy sophisticated applications using advanced unstructured and semi-structured data analysis techniques and utilizing high-performance computing environments. Has the ability to utilize advance tools and computational skills to interpret, connect, predict and make discoveries in complex data and deliver recommendations for business and analytic decisions. Experience with software development, either an open-source enterprise software development stack (Java/Linux/Ruby/Python) or a Windows development stack (.NET, C#, C ). Experience with data transport and transformation APIs and technologies such as JSON, XML, XSLT, JDBC, SOAP and REST. Experience with Cloud-based data analysis tools including Hadoop and Mahout, Acumulo, Hive, Impala, Pig, and similar. Experience with visual analytic tools like Microsoft Pivot, Palantir, or Visual Analytics. Experience with open source textual processing such as Lucene, Sphinx, Nutch or Solr. Experience with entity extraction and conceptual search technologies such as LSI, LDA, etc. Experience with machine learning, algorithm analysis, and data clustering.

Conducts data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions. Proactively retrieves information from various sources, analyzes it for better understanding about the data set, and builds AI tools that automate certain processes. Duties typically include: creating various ML-based tools or processes, such as recommendation engines or automated lead scoring systems. Performs statistical analysis, applies data mining techniques, and builds high quality prediction systems. Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms. Should have prior experience with large data Multi-INT analytics, ML, and automated predictive analytics.

Qualifications

BS 8-10, MS 6-8, PhD 3-5

Peraton Overview

Peraton drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world’s leading mission capability integrator and transformative enterprise IT provider, we deliver trusted and highly differentiated national security solutions and technologies that keep people safe and secure. Peraton serves as a valued partner to essential government agencies across the intelligence, space, cyber, defense, civilian, health, and state and local markets. Every day, our employees do the can’t be done, solving the most daunting challenges facing our customers.

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