Data Scientist

  • Dillard's
  • 1600 Cantrell Road, Little Rock, AR, USA
  • 02/08/2021
Full time Information Technology

Job Description

We’re looking for an innovative, creative, data & technical expert with advanced knowledge in statistical modeling. This role reports into the Manager of Advanced Analytics and Strategic Testing who leads a team of highly motivated Statistical Data Analysts and Data Scientists. This is a great opportunity to mentor and lead Statistical Data Analysts on a truly exceptional team in this exciting and ever growing field to shape and create the best shopping and brand experience for Dillard’s customers.

To apply, please submit a PDF of your resume and a PDF of your cover letter answering the following questions.

1. Tell us why you’re interested in this position. What are you looking for in a career move?
2. Give us your elevator pitch! Why are you a good fit for this position? What skills and abilities do you have that you feel make you qualified?
3. We want to ensure we’re on the same page when it comes to compensation. What is your salary expectation (amount required to move forward with your application)? Is it negotiable?
4. Our team works in our corporate office in Little Rock, AR. Are you local? If not, are you willing to relocate?


  • Work with Analytics Team and additional analysts within the organization to drive, shape and direct the practice of Data Science at Dillard’s
  • Mentor/guide/lead Statistical Data Analysts in the design and execution of their specific analytic tasks
  • Work with Marketing, Merchandising, and Operations areas to analyze current business trends, problems, and strategies to help provide actionable insights for the business including but not limited to visualizations, predictive/statistical models and business process supportive machine learning processes
  • Identify and source data needed to build analytic datasets in support of analysis and modeling activities
  • Utilize Machine Learning to detect trends and develop models that will deliver direct business solutions, especially focusing on solutions for large volumes of data
  • Define metrics that will be used to measure and understand existing and new business processes
  • Work directly with multiple levels of management to present results and recommendations from analysis


  • Authorization to work in the United States without sponsorship
  • Ability to work onsite at Corporate Headquarters in Little Rock, AR
  • Master’s degree or its equivalent in Management Information Systems, Statistical Analysis, Applied Mathematics, or related field of study
  • Strong understanding of Analytic infrastructures/environments
  • 6 or more years of experience working with analytic languages/software (e.g., Python, R, Teradata Warehouse Miner, etc.) and performing data modeling, data mining, and exploratory data analysis (e.g., linear/logistic regression, ARIMA, Cluster Analysis) - applicable master level coursework and degree can be considered for up to 1 year of experience requirement
  • Strong personal drive and motivation; entrepreneurial, and excellent at time management
  • Advanced SQL, Data Modeling for Analytics, Big Data management/concepts
  • Strong command of statistical scripting/programming languages (Python, R, etc.)
  • Strong knowledge and experience working with Machine Learning/Artificial Intelligence methodologies
  • Excellent communication and organization skills
  • Experience presenting to small and large groups of people, both technical experts and business executives
  • Ability to adapt and manage multiple responsibilities in a fast paced Agile work environment
  • A self-starter who is able to work both independently and as part of a team
  • Comfortable interacting professionally with a diverse group, executives, managers, statistical data analysts, subject matter experts, and end users
  • Ability to identify opportunities for improvement and lead change


  • PhD in Management Information Systems, Applied Statistics, Applied Mathematics, or related field of study
  • Strong understanding of Retail Business processes and Digital Marketing

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