Vacancy expired!
- Responsible for applying statistics, machine learning and analytic approaches to answer key intelligence questions, producing results and reusable products that provide real value to military intelligence analysts.
- Recognizes when data science can add value to an intelligence problem, and when it cannot, and can translate an intelligence problem into a data science problem and work with intelligence analysts and leaders to refine understanding of the problem.
- The data scientist is a creative problem solver who thrives when presented with a challenge, is able to analyze problems and strategize for better solutions, and has strong problem-solving skills with an emphasis on production for reuse.
- The successful candidate will develop and refine date sets to achieve stakeholder goals and objectives as requested and specifically:
- work with analysts to interpret analytic results and refine analysis as needed.
- apply machine learning techniques to identify and transform data features, find hidden patterns and trends, build and optimize classifiers, create automated anomaly detection systems, and automate steps of the intelligence process.
- evaluate statistical models to determine the validity of analyses, implement evaluated models into production by collaborating with software developers, periodically re-evaluate and refine machine learning models being used in production.
- coordinate with Data Analysts to refine and implement models and monitor outcomes.
- develop processes and tools to monitor and analyze model performance and data accuracy.
- communicate results and ideas to key decision makers, analysts and other stakeholders.
- advise on the interpretation and use of data intelligence products, quality assessments and applications.
- collaborate with intelligence analysts to understand needs and devise possible solutions.
- conduct technical reviews and develop appropriate materials to training system users and Instructors in preparation of operational deployments.
- assess training requirements based on current system and functional baseline.
- develop training artifacts in support of operations including Standard Operating Procedures (SOPs), and Tactics, Techniques and Procedures (TTPs).
- Must be comfortable working in a dynamic environment with several ongoing concurrent projects; able to multitask, prioritize, and manage time effectively.
- Must have excellent written and verbal communication skills and strong leadership, communications, and professional traits.
- Must be Goal-oriented, encouraging to team and staff and comfortable as a teamplayer, leader and mentor.
- Must possess a drive to learn and master new technologies and techniques; desire to maintain currency on latest industry trends including completing additional training; and be able to articulate trends and potential clearly and confidently.
- DoD TS/SCI clearance
- Requires an MS in Data Science, Statistics, Applied Math, or related field PLUS at leastat least 6 years of experience as member of data science team with at least a portion of the experience within the last 2 years leading data science projects.
- OR Bachelor's degree related to the labor category and an additional 8 years of related senior experience, for a total of 12 years, as a substitute to the Master's degree.
- Two years leading data science projects and five years intelligence analysis experience.
- Languages, Tools, and Techniques: Demonstrated proficiency with R or Python, and SQL to manipulate data and draw insights from large and small data sets.Experience with data visualization tools, such as D3.js, ggplot, Bokeh, etc.Skilled data wrangler. Experience with database solutions including SQL, NoSQL (e.g. MongoDB) and graph (e.g. Neo4j)
- Demonstrated proficiency in a variety of supervised and unsupervised machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Demonstrated proficiency in advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Demonstrated proficiency with common data science libraries.
- Demonstrated proficiency visualizing/presenting data for stakeholders.
- Demonstrated proficiency with MS Office tools including Excel, PowerPoint, and Word.
- Demonstrated proficiency with AWS, in particular products related to analytics, compute, database, developer tools, and machine learning.
Vacancy expired!