SPA Job - 50457538 | CareerArc
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Company: SPA
Location: Alexandria, VA
Career Level: Entry Level
Industries: Manufacturing, Engineering, Aerospace

Description

Qualifications

Required Qualifications:

  • Bachelor's degree in physical science, engineering, or mathematics.
  • Demonstrated experience in operations research or numerical analysis in a technical field.
  • Professional experience using R, Python, or other scripting language and scientific programming and mathematical modeling.
  • Excellent verbal and written communication skills.
  • US Citizen with the ability to obtain and maintain a security clearance throughout employment. 

 

Desired Qualifications:

  • At least 2 years of experience using R, Python, or C+.
  • Master's in physical science, engineering, or mathematics.
  • Department of Defense and/or Department of Navy experience.
  • Active DoD Secret Clearance. 


Responsibilities

Everybody's view of data science is a little different, and we are no exception. In SPA's Veracity Forecasting Group, we view data science as a way of understanding “how the world works.” We make assumptions and models then use data of all sorts to validate or disprove them. Our customers ask tough questions about managing their multifaceted enterprises; we build and operate complex models and simulations to provide the answers that best address the decisions they face.

 

We don't expect you to come in with all of the subject matter expertise needed to completely understand the data analysis or to create models with the fidelity we require. We do expect you to get there quickly, though. We look for traits such as how you solve problems when you're stuck. Do you look for creative ways to apply different techniques from tangential disciplines? Do you crack open a book and teach yourself how to do something new? Do you collaborate with your colleagues? If you take initiatives like these, you would fit in well with our team of analysts.

 

We would love to tell you that we spend all our time developing elaborate algorithms for regression, survival, kernel weighting, etc., but honestly, we spend a lot of time wrangling data. This includes combing data from disparate data systems, manipulating formats, and cleaning—all of which are required to make the modeling happen. For this critical work we need someone who is precise, efficient, and tenacious.


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