Data Scientist - Level 3

Applied Network Solutions•Aurora, CO

33d•$100,000 - $165,000

About The Position

At Applied Network Solutions (ANS), we bring together some of the most curious minds in networking and cybersecurity. ANS was founded to disrupt the status quo. For over 25 years, our team provides expertise in network, system engineering and both offensive and defensive cybersecurity operations. What we do: Our vision is for a future in which talent and customers alike come to ANS because of our reputation for delivering technical excellence, solving our nation's toughest challenges and our ability to exceed expectations. Why ANS: At ANS we value the integrity of your work. We are looking for the right person to plan, analyze, design, develop, test, secure, integrate, implement, operate, and maintain the custom solutions that ANS delivers. Together, let's ensure today is safe and tomorrow is smarter.

Requirements

Active TS/SCI clearance with Polygraph
A bachelor's degree and 10 years of relevant experience. An associate's degree plus 12 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position
Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science
A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university
Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms programming (skill in at least one high-level language (e.g., Python)), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. Experience in more than one area is strongly preferred.

Responsibilities

Devise strategies for extracting meaning and value from large datasets.
Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge.
Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
Employ some combination (2 or more) of the following areas: 1. Foundations (Mathematical, Computational, Statistical) 2. Data Processing (Data management and curation, data description and visualization, workflow and reproducibility) 3. Modeling, Inference, and Prediction (Data modeling and assessment, domain-specific considerations)