Lead Data Scientist in Scottsdale, AZ at Discount Tire Corporate Careers

Date Posted: 10/20/2021

Job Snapshot

  • Employee Type:
    Full-Time
  • Region:
  • Experience:
    Not Specified
  • Date Posted:
    10/20/2021

Job Description

Here at Discount Tire, we celebrate the spirit of our people with extraordinary pride and enthusiasm. As America’s largest independent tire retailer, specializing in tires & wheels, we have over 1,000 store locations and continue to grow every year. Our consistent growth over the last 60 years, the loyalty of our customers and passion of our people makes Discount Tire a great place to work.

 

Even more exciting, Discount Tire is predicting, embracing, and driving the changes expected in the Automotive Industry. Leadership believes Data and Analytics are a competitive advantage. As such, we are leveraging an established world class data environment so that this position can help us to solve a wide range of complex business problems. The Lead Data Scientist leads the efforts to identify use cases from business partners, analyzes and mines very large quantities of data, develops predictive models that solve complex problems, and presents findings to C-Suite executives and other management. This position also oversees the technical work from less experienced data scientists.

 

Essential Duties and Responsibilities:

• Builds and validates predictive models of an ambiguous issue with no initial solution, utilizing large scale data from multiple data sources and ensures adoption of the model. Drives continuous improvement to existing models and reviews other Data Scientists' models.

• Uses machine learning techniques to create data-driven solutions for various business use-cases

• Understands complex business needs and identifies potential use cases in more than one business unit. Works with external partners to develop a minimal viable product to meet those needs while resolving any issues that may arise.

• Leads the analysis and mining of very large quantities of data using a deep knowledge of a specific domain to find patterns and insights utilizing statistical software

• Writes code for the scope of work being done. Assists in development of data science standards for the department.

• Identifies data that is necessary to complete the analysis and improve the validity, predictability, and accuracy of models. Advises technology partners on new data sources and assists in integrating new internal or external data into the data stack.

• Interprets, communicates, and presents analytic results to C-Level executives and below

• Consistently collaborates with fellow data scientists and frequently interacts with business partners, project managers, cross-functional teams, key stakeholders, and other domains to build analytics capabilities and drive business value.

• Mentors and assists in technically supervising less experienced Data Scientists. Continually strengthens knowledge of analytical methods, vendors, and tools and shares knowledge by participating in best practice sharing opportunities

Job Requirements

Qualifications:

  • 6-9 years of data science experience
  • Experience applying statistical techniques in 3+ business units or domains (marketing, pricing, supply chain, operations, etc.)
  • Extensive Experience in Machine Learning
  • 6 years of programming experience in statistical software (for example Python, R, or SAS) and able to demonstrate proficiency at an advanced level. Python expertise is preferred.
  • Ability to work with large data sets from multiple data sources.
  • Ability to communicate complex analytics concepts and techniques to C-Level executives and below
  • Ability to work collaboratively with other data scientists and multiple stakeholders across business unit(s) and with external partners.
  • Intellectual curiosity, a passion for data and a results orientation.

 

Educational Requirements:

Master's degree in a quantitative field including but not limited to data science, analytics, and statistics.

 

Work Days:

Normal work days are Monday through Friday.  Occasional Saturdays and Sundays may be necessary.

 

Work Hours:

Normal work hours are 8:00 a.m. to 5:00 p.m. Additional hours may be necessary