NCIS Data Scientist

Clearance Level
Top Secret/SCI
Category
Software Engineering
Location
Quantico, Virginia

REQ#: RQ46188

Travel Required: None

Join GDIT and be a part of the team of men and women that solve some of the world’s most complex technical challenges. The NCIS program is searching for a Mid-Level Data Scientist to join their team in Quantico, VA.

The Naval Criminal Investigative Service (NCIS) is an organization of over 2,000 personnel of which 700 serve at HQ and the remaining staff serve at offices worldwide. NCIS is the Department of Navy (DON) component with primary responsibility for criminal investigation, law enforcement (LE), counter-terrorism (CT), counterintelligence (CI), and cyber matters.  NCIS not only has primary responsibility for all criminal investigative, CI, CT, and cyber matters within the DON, but it also has exclusive investigative jurisdiction in non-combat matters involving actual, potential, or suspected criminal, terrorism, sabotage, espionage, and subversive activities. 

NCIS provides the DON with threat status and warnings associated with terrorist, criminal, cyber, and counterintelligence activity throughout the world.  NCIS is the only DON organization that has the information and responsibility to fuse and analyze the national intelligence and law enforcement information necessary to provide these warnings.  

This position will support the NCIS Office of the Command Data Officer (OCDO) and will be responsible for advancing the agency’s mission of investigating and defeating criminal, terrorist, and foreign intelligence threats to the DON – in the maritime domain, ashore, and in cyberspace.  The NCIS OCDO is committed to supporting the NCIS mission through the implementation of a modern, integrated internal data infrastructure with a focus primarily on exploiting the established data foundation to make internal and customer-centric business processes as effective and efficient as possible, laying the foundation for cognitive capabilities that can sense and respond to both internal and external customer data needs. The OCDO will also focus on expanding the organization’s data ecosystem to include context-rich data while maintaining the agility needed to spark innovation.

As an integral part of the OCDO, you will perform the following functions: 

Responsibilities

  • Establish shared operational data and integrated enterprise data, all while managing and/or improving data quality and security through the creation of business-driven governance structures and culture change management.
  • Establish data policies, standards, and procedures that improve data quality, availability, accessibility, security, usability, and enforcement of enterprise information management (EIM) program requirements.
  • Establish enterprise standards – including a uniform and repeatable system development lifecycle methodology for Reference Data and Master Data (e.g., a common set of standards for data naming, abbreviations, and acronyms).
  • Develop a data catalog to help NCIS organize and find data stored in their many systems.  The data catalog shall include information about tables, files, and databases from the NCIS Enterprise Resource Planning (ERP), human resources (HR), finance, capability platforms, and social media feeds. The data catalog must also show where all the data entities are located.
  • Develop a Master Data Management (MDM) Plan that focuses on the technology, tools, and processes ensuring master data is coordinated across the NCIS enterprise. MDM is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference. The data that is mastered may include reference data – the set of permissible values, and the analytical data supporting decision making. MDM provides a unified master data service intended to provide accurate, consistent and complete master data across the NCIS enterprise and to business partners.
  • Recommend solutions based on performing industry-specific analysis, such as case studies describing data management best practices, identifying trends across the industry.
  • Optimize and consolidate business and operational data while augmenting it with data about, and often generated by customers. Expand the data infrastructure to include sensor, device data, and other data sources.
  • Make recommendations to improve the efficiency and effectiveness in how NCIS acquires, stores, manages, shares and applies its data.
  • Engage business users and stakeholders for the increased release of actionable high-quality data on key operational and tactical activities at NCIS.
  • Develop technology solutions to provide the platform, training, and standardized tools enabling querying, data mining, statistical analysis, reporting, scenario modeling, data visualization, and dash-boarding, and processes for a centralized, or analytics as a service model, allowing for the sharing of data across the enterprise from a common hub, facilitates cross-organizational data initiatives due to its enterprise-wide view of data assets and needs.
  • Identify and manage risks proactively.

Basic Qualifications

  • Required:  A bachelor’s or master’s degree in computer science, data science, operations research, statistics, applied mathematics, or a related quantitative field [or equivalent work experience such as, economics, engineering and physics] is [preferred/required]. Alternate experience and education in equivalent areas such as economics, engineering or physics, is acceptable. Experience in more than one area is strongly preferred.
  • Required:  Three to six (midlevel) of relevant project experience in successfully launching, planning, and executing data science projects. Preferably in the domains of risk modelling and quality assessment.
  • Preferred:  Specialization in text analytics, image recognition, graph analysis or other specialized ML techniques such as deep learning, etc.
  • Preferred:  the candidates are adept in agile methodologies and well-versed in applying DevOps/MLOps methods to the construction of ML and data science pipelines.
  • Coding knowledge and experience in several languages: for example, R, Python, Java, C++, Excel, MATLAB, etc.
  • Experience with popular database programming languages including SQL, PL/SQL, others for relational databases and upcoming non-relational databases such as NoSQL/Hadoop-oriented databases such as MongoDB, Cassandra, others.
  • Preferred:  Specialized/operational data scientists may need further high-performance computing (HPC)/compute skills; larger data science teams, in particular, may require further degrees of specialization such as:
    • Experience with distributed data/computing tools such as MapReduce, Hadoop, Hive, Kafka, and MySQL
    • Experience of working across multiple deployment environments including cloud, on-premises and hybrid environments, multiple operating systems and through containerization techniques such as Docker, Kubernetes, AWS Elastic Container Service, and others.
    • Experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
    • Preferred:  Expertise in solving vision, text analytics, credit scoring, and failure prediction problems.
    • Knowledge and experience in statistical and data mining techniques such as generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
  • Strong documentation skills. 
  • Proficient in information security, information assurance, information technology, and cyber defense best practices and principles
  • Required:  Certifications as per Cybersecurity Workforce Management and Qualification Manual, SECNAV M-5239.2.
  • Required:  candidates can be SCI-eligible, but must have their SSBI at a minimum of SECRET.

We are GDIT. The people supporting some of the most complex government, defense, and intelligence projects across the country. We deliver. Bringing the expertise needed to understand and advance critical missions. We transform. Shifting the ways clients invest in, integrate, and innovate technology solutions. We ensure today is safe and tomorrow is smarter. We are there. On the ground, beside our clients, in the lab, and everywhere in between. Offering the technology transformations, strategy, and mission services needed to get the job done.

GDIT is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status, or any other protected class.