The Data Science Division (DSD) is part of the Center for Naval Analyses. The mission of the DSD is to develop innovative, cutting-edge analytics that are relevant, impactful, and actionable.
The DSD provides data science expertise and support to the Department of the Navy and Department of Defense. The division collaborates with our sponsors to transform their operations by making data and analytics an integral part of their decision-making. As part of the Navy’s only dedicated FFRDC, we use our analytic skills and our knowledge of naval operations to help create a competitive advantage for the Navy. That advantage has never been more critical than it is today, with great power competition challenging the Navy in several concurrent theaters and across all warfighting domains.
The division has full time and part time analysts with advanced degrees in data science, operations research, statistics, economics, computer science, physics, mathematics, engineering, chemistry, and other technical disciplines. The Data Science Division has a large set of core technical competencies, including:
- Developing supervised and unsupervised machine learning models, such as artificial neural networks, random forests, and clustering, to predict outcomes and assist decision-makers
- Leveraging high performance computing to obtain insights from big data
- Developing custom analytical simulations using techniques such as continuous time, discrete event, and Monte Carlo approaches to approximate existing systems to quantify the effects of changes to improve those systems
- Building and deploying dashboards and dynamic decision support tools in the Navy’s cloud environments
- Identifying optimal solutions using mathematical programming techniques such as mixed integer programming, network analysis, and linear/non-linear programming.
- Leading and facilitating human centered design workshops to ensure data-driven solutions meet stakeholder requirements and preferences
The DSD develops models and analytics to support Navy problems across all Navy domains, including aviation, surface warfare, undersea warfare, cyber, logistics, readiness, force generation, sustainment, acquisition, and cost modeling. DSD analysts support decision-makers by identifying key drivers of both successful and poor performance to improve Navy and Marine Corps outcomes. The division currently supports the Navy’s Performance-to-Plan forum, which provides senior Navy leadership forward‑looking performance forecasts, which are foundational to articulating Navy progress toward readiness and capability goals. Projects generally involve large datasets and complex questions that demand advanced coding skills as well as statistical and modelling techniques. The division leverages agile project management techniques to support faster cycle times to insights and to develop analytic minimum viable products.
CNA fosters an inclusive culture that values diverse backgrounds and perspectives. Our flexible and engaging work environment encourages iterative and creative collaboration at every stage of the problem solving process. Our employees are committed to helping clients develop effective solutions to better manage their programs through scientific, data-driven approaches.
Data Analysts II in the Data Science Division work on projects to develop advanced analytics and algorithms for the Department of the Navy and other government agencies to ensure America’s defense in the 21st century. Data Analyst II apply CNA’s unique approach to analytics that combines an understanding of the technical data science capabilities with experience from military exercises, operations and sponsors.
1. Leverage R and/or Python to develop machine learning models for, e.g., regression, classification, natural language processing, and/or image recognition.
2. Familiarity with Navy and Marine Corps operations, maintenance, supply, training, and personnel datasets.
3. Extract, transform, load (ETL) data from various data sources in order to initiate analysis.
4. Conduct data preparation including cleaning, wrangling, joining, and converting data in order to provide a useable analytic dataset.
5. Conduct Exploratory Data Analysis (EDA) to include the use of data visualizations (e.g. Dash, MATPLOTLIB, R Shiny, ggplot2, Power BI, etc.), correlations, empirical/theoretical distributions of data, and summary statistics.
6. Apply statistical methods including descriptive and inferential techniques using parametric and nonparametric statistics.
7. Communicate analysis and results clearly, concisely and precisely for colleagues and clients.
8. Contribute to the completion of milestones associated with specific projects by analyzing complex datasets and using effective visualizations of data in their results. Establish short-term goals and objectives within sphere of responsibility; help provide a leadership role in developing alternative and new analytic paths.
9. Serve as an effective team member and may lead a portion of a small project by fulfilling assignments in a timely and efficient manner. Works cooperatively by providing clear input to colleagues on tasks. Exhibit a positive attitude, and takes responsibility for own actions and outcomes.
10. Interacts effectively with personnel across the FFRDC. Develops professional and enduring relationships with functional peers within the organization, as well as sponsors / clients/ vendors; sometimes with guidance from others. Interaction normally involves exchange or presentation of factual, but somewhat varied and complex information.
11. Perform other duties as assigned.
1. Education: Bachelor’s degree in Data Science, Operations Research, Computer Science, Math, Statistics, or related field or equivalent combination of education and work experience
2. Experience: Minimum 2 years relevant experience. Experience with Department of Defense (DOD), the military branches or other government agencies preferred.
3. Skills: Proficient in applying machine learning techniques, building models (statistical, mathematical, simulation, etc.) in programming languages such as R or Python. Ability to analyze complex datasets using effective visualizations of data in achieved results; skilled in programming, statistics, machine learning, and data visualization. Working knowledge of data and information management analysis techniques and best practices. Experience working in cloud data environments such as AWS and Azure desired. Ability to work with ML tools such as Spark, Databricks, and Data Robot. Ability to construct effective briefings using MS PowerPoint and intermediate to advanced skills with MS Word and Excel and other standard software packages. Ability to communicate information effectively in both oral and written communication. Ability to present and summarize data effectively. Works effectively on a team and able to build rapport with colleagues, clients/sponsors, and staff. Strong customer and client relations skills.
4. Other: Ability to obtain and maintain an Active Security Clearance.
1. Cover Letter – Please include a cover letter as part of your application to be considered for this position. A cover letter should introduce yourself, briefly summarize your professional background, explain why you are a good candidate and the reason for your personal interest in applying for this job.
2. Transcripts – Please include your transcripts as part of your application to be considered
***Voluntary (but highly desired) document***
Please include a personal statement as part of your application. A personal statement is a chance for us to get to know you. The statement is your opportunity to share your goals, interests, influences and show us that you will be a valuable asset to our organization. Please click here for personal statement guidelines – Click here
Personal statements will not be used as an elimination criteria for this position. They will only be used to enhance a candidate’s application.