Senior Data Scientist

*This is to pipeline candidates for upcoming work to be awarded at a future date*Job Duties:Involved in the analysis of structured, 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 advanced tools and computational skills to interpret, connect, predict, and make discoveries in complex data and deliver recommendations for business and analytic decisions.Required Skills:Must be a U.S. CitizenTS/SCI Clearance with polygraphMinimum 5 years of experienceBachelor's degree in Computer Science or related fieldExperience with software development, either an open-source enterprise software development stack (Java/Linux/Ruby/Python) or a Windows development stack (.NET, C#, C++).Desired Skills:Experience with NVIDIA Technology & frameworksExperience 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.Ability to build Python scripts and packages that will be used by the data analysts. The Python scripts will use supervised and unsupervised ML (both text and image-based machine learning), natural language processing (named entity extraction, summarization, etc.), and network analysis (social network analysis, centrality analysis, dynamic network analysis).Expertise in maintaining and deploying a notebook-based data science environment (JupyterHub).Experience in advanced Python data science packages (Pandas, NetworkX, Scikit-Learn, PyTorch or TensorFlow/Keras, Matplotlib or Plotly, etc.)

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