Data Scientists in the NFL: An Example

A few weeks ago, I wrote about an example of data science in basketball (link).

This week, the Philadelphia Eagles (link) have provided an example from the NFL. They have advertised three posts:

Director of Analytics – Football Operations (link)

Senior Quantitative Analyst – Football Operations (link)

Quantitative Analyst – Football Operations (link)

The Director of Analytics will “work closely with the VP of Football Operations and Strategy to shape analytics within Football Operations”. The position description includes the following:

The Director of Analytics will use data to address key issues in the modern NFL front office including player evaluation, game preparation, resource allocation, sports science, and player development. A strong candidate will have significant work experience, an advanced degree in a quantitative discipline, and a demonstrated ability to interact with a diverse set of stakeholders. We will prioritize applicants with deep knowledge of modern statistical techniques and the creativity to identify novel analytical directions. The position requires strong organization, communication, and leadership skills, and the ability to work on widely varying projects with distinct audiences.

Candidates for the position “must have the ability and statistical range to draw insights from many different forms of football data and a passion for improving football decision-making”.

The qualifications expected of candidates for the Director’s role are:

  • Outstanding analytical and quantitative skills
  • 3 – 5 years of significant work experience
  • Advanced degree with strong performance in statistics, machine learning, or econometrics
  • Excellent at data management and statistical analysis
  • Experience with multiple statistical software packages and/or programming languages
  • Strong communication skills, both verbally and in writing
  • Vision to plan for and adapt to changes in available football data
  • Football knowledge to identify key questions and topics for analysis

The Senior Analyst “will have relevant work experience and/or graduate-level training in a quantitative discipline”. Applicants for the post “should have a deep understanding of modern statistical techniques, with proven ability to execute on their ideas”. Candidates will be expected “to be well-versed in sports analytics research and methods”. The qualifications listed for the position:

  • Outstanding analytical and quantitative skills
  • 2-3 years of relevant work experience or comparable academic experience
  • Advanced degree in statistics, machine learning, or econometrics
  • Highly skilled in statistical software for data management and analysis
  • Software development and data visualization skills are a plus
  • Ability to communicate complex ideas to diverse audiences
  • Passion for football

The Analyst “will be able to work with football data to draw insights and improve decision-making”. Applicants should have “the quantitative skills to analyze complex problems and the technical ability to implement their ideas effectively”. Candidates will be expected applicants to have a solid foundation in statistical modeling.  The qualifications listed for the position:

  • Undergraduate or graduate degree in a relevant field
  • Strong analytical and quantitative skills
  • Experience in statistics, machine learning, or econometrics 
  • Proficient with data management and analysis in statistical software (e.g. R, STATA)
  • Software development and data visualization skills are a plus
  • Good communication skills
  • Ability to work independently with a hands-on approach.
  • Passion for football 

Photo Credit

What’s understood doesn’t need to be explained (Twitter)

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