Job description

Requirements Data Scientist Labor Category – Level: Data Science, Analytics, and Algorithms – Full Performance Status: Vacant – Immediate Need Location: Chantilly Schedule: M-F; Core Hours (9am-3pm) Work Space: Permanent desk will be assigned upon arrival Summary In this dynamic role, you will join a top-tier team of Information Technology and Analytic professionals dedicated to supporting national security through innovative data science and analytics. You will work in a self-contained Big Data environment where the team manages everything from infrastructure and application development to advanced analytics. This position offers numerous opportunities for growth, collaboration, and problem-solving in a thought-provoking, mission-driven setting. Duties, Tasks & Responsibilities Working with large, complex, and disparate data sets Designing and implementing innovative ways to analyze and exploit the Sponsor’s data holdings Researching and reporting on a wide variety of Sponsor inquiries Raising proactive inquiries to the Sponsor based on observations and proposed data analysis/exploitation Solving difficult, non-routine problems by applying advanced analytical methodologies, and improving analytic methodologies Developing custom searches Participating in threat hunting and/or developing advanced, novel detection mechanisms to counter malicious actors Required Experience, Skills, & Technologies Thorough knowledge of appropriate analytic tools and methodologies in one or more of the following: Applied mathematics (e.g. probability and statistics, formal modeling, computational social sciences) Computer programming (e.g. programming languages, math/statistics packages, computer science, machine learning, scientific computing) Ability to code or script in one or more general programming language Experience with, and understanding of, algorithms for classification, regression, clustering, and anomaly detection Knowledge of relational databases, including SQL and large-scale distributed systems (e.g. Hadoop) Expertise with statistical data analysis (e.g. linear models, multivariate analysis, stochastic models, sampling methods) Demonstrated effectiveness in collecting information and accurately representing/visualizing it to non-technical third parties Desired Experience, Skills & Technologies Experience working in a mission environment and/or with many different types of data Familiarity with building MVP/Prototype data engineering pipelines to support novel analytics Experience in signature development, threat hunting, and/or threat modeling Background in computer network operations, particularly network defense and/or exploitation

Requirements

Must-haves

Data Scientist
Labor Category – Level: Data Science, Analytics, and Algorithms – Full Performance
Status: Vacant – Immediate Need
Location: Chantilly
Schedule: M-F; Core Hours (9am-3pm)
Work Space: Permanent desk will be assigned upon arrival
Duties, Tasks & Responsibilities
Working with large, complex, and disparate data sets
Designing and implementing innovative ways to analyze and exploit the Sponsor’s data holdings
Researching and reporting on a wide variety of Sponsor inquiries
Raising proactive inquiries to the Sponsor based on observations and proposed data analysis/exploitation
Solving difficult, non-routine problems by applying advanced analytical methodologies, and improving analytic methodologies
Developing custom searches
Participating in threat hunting and/or developing advanced, novel detection mechanisms to counter malicious actors
Required Experience, Skills, & Technologies
Thorough knowledge of appropriate analytic tools and methodologies in one or more of the following:
Applied mathematics (e.g. probability and statistics, formal modeling, computational social sciences)
Computer programming (e.g. programming languages, math/statistics packages, computer science, machine learning, scientific computing)
Ability to code or script in one or more general programming language
Experience with, and understanding of, algorithms for classification, regression, clustering, and anomaly detection
Knowledge of relational databases, including SQL and large-scale distributed systems (e.g. Hadoop)
Expertise with statistical data analysis (e.g. linear models, multivariate analysis, stochastic models, sampling methods)
Demonstrated effectiveness in collecting information and accurately representing/visualizing it to non-technical third parties
Desired Experience, Skills & Technologies

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

machine learningsql

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