35 applicants

Company

Original Job Post

Boeing Intelligence & Analytics · 3 days ago

Data Scientist - Mid Level

Virginia, United States

Full-time

Hybrid

Mid, Senior Level

$153K/yr - $180K/yr

9+ years exp

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Information TechnologySoftware

Comp. & Benefits

Hiring Manager

Don Caluya

Insider Connection @Boeing Intelligence & Analytics

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Involvement in the analyses of unstructured and semi-structured data, employing advanced techniques such as latent semantic indexing (LSI), natural language processing (NLP), and exploratory data analysis (EDA).

Utilizing non-traditional approaches to analyze large-scale unstructured data, visualizing results through multi-dimensional interfaces.

Researching and testing novel machine learning approaches for analyzing large-scale distributed computing applications.

Collaborating with a dynamic team to suggest innovative concepts and ideas to improve the overall platform.

Leveraging strong technical and computational skills to interpret complex data and deliver recommendations for business decisions.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

TS/SCI ClearancePolygraphData TransportAPIsJSONXMLXSLTJDBCRESTCloud-Based Data AnalysisHadoopMahoutAcumuloHiveImpalaPigVisual Analytic ToolsMicrosoft PivotPalantirVisual AnalyticsOpen-Source Textual ProcessingLuceneSphinxNutchSolrEntity ExtractionConceptual Search TechnologiesLSILDAMachine Learning

Required

Bachelor's degree in data science, data analytics, computer science, software engineering, or related field, with 9+ years of relevant experience. Additional experience may be considered in lieu of a degree.

Active TS/SCI clearance with the ability to pass a polygraph.

Full-time work in a SCIF is required, with flexible hours.

Experience with data transport and transformation APIs and technologies such as JSON, XML, XSLT, JDBC, and REST.

Experience with Cloud-based data analysis tools including Hadoop, 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.

Experience with Python scripting, Pandas, Excel, and Jupyter Notebooks.

Strong testing and verification skills.

Ability to work in a fast-paced, high visibility environment.