Allied Minds

HawkEye 360 - Junior Data Scientist

US-VA-Herndon
2 weeks ago(1/8/2018 8:35 AM)
Job ID
2018-1186
HawkEye 360
# of Openings
1
Category
Engineering

Overview

 

 HawkEye 360

**This position may require exposure to information which is subject to US export control regulations, i.e. the International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). All applicants must be U.S. persons within the meaning of U.S. regulations.**

 

Put Your Creativity to Work

HawkEye 360, a developer of space-based radio frequency (RF) mapping and analytics systems, is currently seeking a Junior Data Scientist.  As a member of the data analytics team, the engineer will design, implement, support and utilize a scalable analytics architecture and complementary analytic products. 

Team members will invent and produce processing components within the analytics architecture to derive data products with commercial potential on topics ranging from behavior characterization and geospatial prediction to visual data representation. The analytics team will take the lead integrating processed data and analytic products with systems developed by customers and partners.

The Junior Data Scientist will play an essential role in developing and maintaining a scalable analytics architecture and ensuring data perseverance and integrity. Reporting to the Director of Analytics, the Junior Data Scientist will also have the opportunity to contribute to analytic or machine learning product development.

Responsibilities

We’ll Expect You To…  

  • Derive and implement analytic components to predict or detect behaviors of interest; predict or determine spectrum usage patterns; develop profiles for RF-emitting actors, or to answer similar and related questions using statistical and machine learning methods
  • Select features, build and optimize classifiers using machine learning techniques
  • Extend the company’s data with third-party sources of information when needed
  • Develop visualizations and other analytic end products
  • Coordinate with the signal processing team to develop shared interfaces and formats for supported datatypes. Specify RF data processing requirements for analytic products and direct RF tasking
  • Conduct data mining using state-of-the-art methods
  • Enhance data collection procedures to include information that is relevant for building analytic systems
  • Process, cleanse and verify the integrity of data used for analysis
  • Create automated anomaly detection systems and constant tracking of its performance

Qualifications

You’ll Need to Have…

  • 3-7 years professional experience with data analytics or equivalent professional experience as a software developer for quantitative applications
  • S. or higher in electrical and computer engineering, statistics, mathematics, physics or another quantitative field with relevant work in statistical modeling, machine learning or data analytics contributing to that degree. Particularly strong work experience may be deemed equivalent for candidates with alternative or lesser degrees
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
  • Demonstrated effective experience with computational statistical methods and modeling or machine learning using some combination of Python, C/C++ and Java
  • Experience with common data science toolkits
  • Experience blending analytic and simulation modeling approaches to problem solving
  • Experience with data visualization tools, such as D3.js, GGplot, etc.
  • Proficiency in using query languages such as SQL, Hive andPig
  • Experience with NoSQL databases, such as MongoDB
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Good scripting and programming skills.
  • Data-oriented personality

We’d Like to See…

  • Relevant experience with statistical modeling or machine learning.

Options

Sorry the Share function is not working properly at this moment. Please refresh the page and try again later.
Share on your newsfeed