Data Scientist IV

Arcfield•McLean, VA

About The Position

Arcfield is seeking a Data Scientist to collaborate with a team in solving complex problems, with considerable latitude in determining objectives and approaches to assignments. The role supports mission and targeting needs by identifying and exploiting data sources, developing data-driven solutions and analytical methods, and working with government, contractor, and other partner personnel. The position involves processing high-volume data collections and high-velocity data streams, integrating and analyzing complex data, and presenting useful results through accessible interfaces and visual analytics.

Requirements

Must possess and be able to maintain a TS/SCI clearance with Polygraph.
Bachelor’s degree or equivalent experience in Computer Science, Information Systems, Engineering, Business, or a related scientific or technical discipline.
Experience: BS 8–10 years, MS 6–8 years, or PhD 3–5 years.
Knowledge of the Sponsor’s environment.
Experience working with sensitive commercial partners and commercial data sets.
Experience presenting data analysis results to drive technical development and inform decision-making.
Experience with software development environments, including open-source enterprise software stacks such as Java, Linux, Ruby, or Python, and Windows development stacks such as .NET, C#, or C++.
Experience with data transport and transformation technologies and APIs, such as JSON, XML, XSLT, JDBC, SOAP, or REST.
Experience with cloud-based and distributed data processing and analytics technologies, such as Hadoop, Mahout, Accumulo, Hive, Impala, or Pig.
Experience with visual analytics tools, such as Microsoft Pivot, Palantir, or other visual analytics platforms.
Experience with open-source text processing and search technologies, such as Lucene, Sphinx, Nutch, or Solr.
Experience with entity extraction, conceptual search, and semantic analysis techniques, such as Latent Semantic Indexing (LSI) and Latent Dirichlet Allocation (LDA).
Experience with machine learning, algorithm development and analysis, and data clustering techniques.
Experience with data science tools, techniques, and methodologies.

Nice To Haves

Ability to work with data sets across different computer systems, networks, and organizations.
Strong interpersonal and communication skills.
Ability to work effectively with cross-functional teams and stakeholders.

Responsibilities

Leverage new data sets, identify new applications, develop innovative targeting methodologies, and collaborate with internal and external stakeholders on data-driven solutions for the Sponsor’s highest-priority mission needs.
Identify, assess, and exploit relevant data streams to support mission and targeting requirements.
Design and implement real-time data processing techniques to address immediate needs.
Develop user-friendly data interfaces for stakeholders unfamiliar with the data, including targeters and engineers.
Integrate multiple data streams to create a unified view of complex data sets.
Develop and implement data science techniques to detect identified signatures in large data sets.
Use diverse data sources to enhance the value and utility of new data sources.
Support multiple high-priority customers with varying requirements.
Collaborate with government, contractor, and non-IC partner personnel.
Troubleshoot data processing issues across networks and optimize data delivery and formats.
Engage with stakeholders to develop solutions based on prioritized requirements.
Analyze unstructured and semi-structured data using techniques such as latent semantic indexing (LSI), entity identification and tagging, and complex event processing (CEP), and apply analysis algorithms across distributed, clustered, and cloud-based high-performance infrastructures.
Apply non-traditional approaches to large-scale analysis of unstructured data in support of high-value use cases visualized through multi-dimensional interfaces.
Handle, process, and index requests against high-volume data collections and high-velocity data streams to identify meaningful insights and discoveries.