The Institute for Defense Analyses (IDA) is a Federally-Funded Research and Development Center supporting the Department of Defense (DoD) and other federal agencies. IDA takes great pride in the high caliber and timeliness of its analyses, which are produced in an atmosphere that encourages collaboration, independent thinking, and objective results.
The Cost Analysis and Research Division (CARD) at IDA engages in both traditional cost analysis and applied research on a broad range of topics involving resource allocation, forecasting, econometrics, and systems modeling. CARD researchers perform a wide variety of quantitative analyses that clearly illuminate the resource and outcome consequences of government decisions, policies, and actions. As studies often require a multi-disciplinary approach, CARD maintains a highly educated and diverse research staff with advanced degrees in many quantitative fields, including various branches of engineering, operations research, statistics, economics, mathematics, physics, and natural sciences.
The Institute for Defense Analyses (IDA) seeks a data scientist with expertise in machine learning and predictive analytics to join the Research Staff of the Cost Analysis and Research Division (CARD). The Senior Data Scientist will apply modern data analytics techniques in support of CARD projects and analyses. Analytical tasks will include data characterization, clustering, statistical inference, stochastic modeling, data mining, forecasting, text analysis, and feature extraction in diverse data sets. The Senior Data Scientist will also be expected to interact with study sponsors, summarize findings for nontechnical audiences, and write reports and present briefings in a clear and concise manner suitable for senior DoD policy makers.
- A Ph.D.in Operations Research, Statistics, Computer Science, Research Psychology, Economics,Applied Mathematics, or a Master’s Degree in a data analytics field listed combined with 10+ years of relevant experience.
- Proven expertise with machine learning and predictive analytics is required.
- Preferred areas of interest include classical and Bayesian statistics, Bayesian inference networks, deep learning, stochastic processes, econometrics, text analytics, and knowledge representation.
- Desired skills include programming in multiple languages (e.g., R, Python), working with large data sets, data collection, data normalization, and data visualization.
- Candidates should have the ability to work both independently and collaboratively, and exhibit strong communications skills.
- U.S. citizenship is required and applicants must meet the eligibility requirements for access to classified information.