Data Science – Advisor

Data Science – Advisor

Requirements

• Minimum of 8 years with BS/BA; Minimum of 6 years with MS/MA; Minimum of 3 years with PhD
• Requires current TOP SECRET/SCI Clearance with Poly
• Demonstrated experience in the following: Developing python and bash scripts, Developing dockerfiles and running docker containers both isolated and as networked services, Use of git technologies to include hub and lab, Write analytics, algorithms, or models in time series, text analytics, cyber/network analysis, Authoring CI/CD jobs in jenkins groovy or gitlab CICD YAML, Managing non-person-entity (NPE) certificates, Writing or extending libraries of cross-boundary deployments via CI/CD workflows.

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.
• Handles 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).
• 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.

Preferred Qualifications

• AWS
• Machine Learning
• AI Planning
• Multi-Factor TLS
• Authentication/Authorization
• Model Management to include versioning, artifact generation, and ephemeral validation