Data Analytics/Machine Learning Professional

US-MS-Vicksburg
7 months ago(5/11/2017 11:12 AM)
Requisition ID
2017-27015
# of Openings
1
Category
Information Technology
Minimum Clearance
Secret
Relocation Eligible
No

About Engility

Engility delivers innovative solutions to critical challenges facing the nation and the world. As a premier provider of integrated services for the U.S. government, we support the Department of Defense, intelligence community, space communities, federal civilian agencies and international customers. Engility is dedicated to making lives better, safer and more secure.

Description

Engility is recruiting for a Data Analytics/Machine Learning Research Scientist for the PETTT HPC Program.

 

Responsibilities include, but not limited to:

  • Provide on-site support to DoD High Performance Computing (HPC) users in the area of Big Data Analytics with a primary focus on Python based tools, including machine learning/deep learning, neural networks and Bayesian methods, and applied areas such as cyber analytics or computer-vision (image representation, object recognition, and caption generation). Provide advanced science level support to DoD HPC users.
  • Interact with members of the DoD HPC community and senior members of the DoD S&T community where HPC can be applied to domains of interest to DoD, e.g., high throughput screening, automatic target recognition (ATR), autonomy and other emerging areas.
  • Upon identification of requirements and promising research approaches the successful candidate will work with team members on the development and implementation of new work-stream tools to promote the adoption of high performance data analytics (HPDA) within the DoD HPC community. This includes science gateways, interactive capabilities, databases, custom tools installation and integration, optimization, data manipulation, data formats and management, and data mining, as well as leveraging new technologies such as containers. The ideal candidate will have the ability to prototype new solutions that work in restricted environments on DoD HPC systems and troubleshoot underlying technologies such as network and login processes, web technologies, and data management frameworks.

 

Secret clearance is required to start, we will process for the right candidate.  Relocation assistance is available.

Required Qualifications

  • Education: Master’s Degree in computer science or data science related area at least 7 years of relevant work experience.
  • Proficient in high performance Python and Python based data analytics tools such as parallel python packages, Pandas, Numpy, SciPy, Scikit-learn, and Matplotlib.
  • Strong background in one or more data science areas, such as math/statistics, machine/deep learning, data mining, data management, web technologies, or databases.
  • Strong software prototyping tool development and bash scripting experience on Linux systems.
  • Strong understanding of big data concepts and familiarity with Apache Big Data Stack tools, particularly Spark, but also others such as Kafka, Storm, Pig, Mahout, Hive, etc.
  • Excellent communication, presentation, and collaboration skills.

Desired Qualifications

  • Education: PhD in computer science or data science area with 5 or more years of work experience.
  • Strong background in distributed or parallel computing with experience in parallel python packages, MPI, or other distributed computing frameworks.
  • Proficient at building and deploying Python packages with the Conda environment and interfacing with C/C++ codes.
  • Proficient in other data science supporting languages such as R, SQL, Java, Javascript, Octave, Matlab, or Ruby.
  • Software prototyping tool development experience in High Performance Computing environments with batch schedulers.
  • Experience with deep learning frameworks, particularly TensorFlow or Caffe, but also others such as Keras, Theano, or Torch.
  • Experience with developing and deploying container based data analytics workflows, particularly in parallel, such as with MPI frameworks.
  • Familiarity with agile software development practices.

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