American Fidelity – Hiring Data Scientists

By | March 7, 2019

American Fidelity Now Hiring Data Scientists.

Listed as one of the 100 Best Companies to Work for in the country by Fortune magazine and the Great Place to Work Institute, American Fidelity is looking for Data Scientists to join their Enterprise data team and their recruiters have contacted the University of Oklahoma, and the MS Data Science and Analytics program in particular, looking for candidates.

If you are interested you can (1) Apply for the job here, and/or (2) contact Dr. Nicholson for more information, and/or (3) if you are a member of the OU Data Science and Analytics Association (BTW free to join and cool people to know!) then you can go to the DSAA Facebook page where I will post the recruiter’s contact information.

Job Description

  • Work with large, complex data sets using to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed to complete end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
  • Engineer analysis pipelines interactively to provide insights at scale. Develop comprehensive understanding of data structures and metrics, advocating for changes where needed in systems, products and processes.
  • Research and engineer analysis, forecasting, machine learning, deep learning, neural networks, artificial intelligence and optimization methods to improve the quality of products; example application areas include customer segmentation modeling and end-user behavioral modeling/prediction.


    • Expert in multiple statistical software (e.g., R, Python, Julia, MATLAB, pandas) and associated data science libraries (scikit-learn).  Note from Professor Nicholson: Ah ha! ISE/DSA 5103
    • Expert in database languages (e.g., SQL).
    • Experience creating meaningful data visualizations and/or interactive dashboards that communicate findings and business impacts using platforms such as Tableau, Qlik, Power BI, RShiny, plotly, and d3.js.
    • Applied experience with machine learning on large datasets using Big Data tools such as Apache’s Hadoop or Spark
    • Expert in deep learning techniques and neural networks using languages such as TensorFlow
    • Expert in multiple major programming language (C/C++. C#, Java, Python, etc.) or optimization modeling languages (AMPL, GAMS, AIMMS, OPL, etc.) Note from Professor Nicholson: What! ISE/DSA 5113 — Python and AMPL!
    • Experience with data science methods related to data architecture, data cleaning, data and feature engineering, and predictive analytics. Note from Professor Nicholson: ISE/DSA 5103 — you got this!
    • Strong background in modeling large scale discrete, nonlinear or stochastic mathematical optimization models and engineering efficient optimization algorithms.
    • Familiarity with natural language processing, machine learning, statistical modeling, predictive modeling, and hypothesis testing.
    • Familiarity working with both structured and unstructured data, including textual data.  Note from Professor Nicholson: Sai Bhavaraju just gave a seminar on NLP with unstructured text data for the OU Data Science and Analytics Association!
    • Ability to work in a fast-paced environment.  Note from Professor Nicholson: If you survived ISE/DSA 5103 and/or 5113, then you are probably ready for this!
    • Exceptionally strong communication skills, including written, verbal and listening which can be deployed successfully when addressing entry level Colleagues to management to senior executives. This includes the ability to speak confidently in both business and technological surroundings and appropriately transliterate between the two.  Emphasis added by Professor Nicholson.
    • Exceptional analytical thinking and problem-solving skills.  Emphasis added by Professor Nicholson.
    • Exceptional understanding of business and business strategy.
    • Exceptional planning skills.
    • Exceptional organizational skill and ability to work autonomously.