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. In particular, Data and Analytics are seen as our competitive advantage. As a Senior Data Analyst, you will be central in helping our company Executives address short term and long-term opportunities to support with strategic data-oriented, actionable insights and solutions related to Discount Tire’s complex business involving large numbers of people, properties and digital assets. We sell tires and wheels from around the world to millions of customers in our stores and through our website. Unlike traditional retail, customers expect us to do more than simply sell them, tires and wheels. We service their vehicles too, making for even more interesting & complex analytics challenges. Additionally, you will collaborate with a multi-disciplinary team of solution architects, engineers and data scientists on a wide range of business problems. Business groups supported include, but not limited to, store operations, real estate, and finance. In this role, you will actively be involved in shaping the company strategy.
As a Senior Data Analyst, you will collaborate with a large, multi-disciplinary team of data engineers, data analysts, and data scientists on a wide range of business problems. You will not only work on multiple projects to provide value to the customers but are also routinely involved in helping to building our internal capabilities to have an edge in the analytics industry. We work on providing solutions to a wide range of internal customers across the organization including senior executives to middle management coming from various domains including, but not limited to retail, manufacturing, store operations, automotive, real estate, or services.
Essential Duties and Responsibilities:
- Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Work on advanced analytics areas like deep learning and complex statistical data analysis
- Interaction with senior leadership and other business leaders to provide business recommendations with effective presentations of findings, including visual displays of quantitative information
- Develop analysis, forecasting and optimization methods/models to provide the business solution to internal customers
- Research and develop internal capabilities to enhance the skill-sets on latest data science developments, work towards producing innovative solutions to the existing challenges
- Perform quality control of deliverables
- Provide thought leadership in algorithmic and process innovations, and contribute to creativity in solving unconventional problems
- Stays current on the latest industry technologies, trends and strategies.
- Other duties as assigned.
- Experience with writing SQL queries, performing basic conversion and transformations (e.g. formatting date string), and obtaining statistical summaries by using windowing functions.
- Experience with usage of R/RStudio, Python, Jupyter Notebook
- Experience with version control tool like Git
- Strong experience with Excel and PowerPoint to present results
- Ability to write scripts to automate ETL tasks
- Ability to run standard model algorithms in Python, to perform: classification/regression, clustering, basic text analytics, image recognition, etc. E.g. run a classification problem using random forest, and obtain the variable importance, produce performance metrics/KPIs; run a k-means clustering problem, produce a KPI to quantify the goodness of clusters
- Demonstrated skills in selecting the right statistical tools given a data analysis problem
- Experience with charting tools & knowledge of the proper charting tool to use, such as Excel. For instance, when to use box-and-whiskers plot, when to use waterfall. Ability to zoom-in to smaller data sets or display subcategories
- Capable of running multiple scenarios and pick up the optimal solution
- Capable of understanding advanced mathematical or physical explanations, to implement or execute the requested tasks. E.g. Fourier Transform, Power Spectral Density, Monte Carlo simulation, etc.
- Actively participates and contributes in brain-storming session. Can work seamlessly with people from other disciplines: IT engineers, SMEs, stakeholders.
- Experience articulating business questions and using mathematical techniques to arrive at an answer using available data. Experience translating analysis results into business recommendations
- Experience in AI / Deep Learning for text/image/video analytics preferred
- Experience in Cloud Computing and data streaming preferred
Team & Business Skills
- Consistently improves communication skills, both verbally and in written materials
- Demonstrated creativity in problem solving
- Demonstrated leadership and self-direction. Demonstrated willingness to both teach others and learn new techniques.
- Flexibility in task switching. For instance, when there is urgent requests or change of projects, can accommodate the changes without protesting
- Mindful of iterations and quality check in a smaller team, before presenting results to larger audience
- Raises critical issues when detected
A Master’s degree in a quantitative discipline (e.g., analytics, statistics, computer science, data science, economics, mathematics, physics, electrical engineering, industrial engineering, or other STEM fields)
5+ years of relevant work experience in data analysis or related field. (e.g., as a statistician / data scientist / data engineer).
Normal work days are Monday through Friday. Occasional Saturdays and Sundays may be necessary.
Normal work hours are 8:00 a.m. to 5:00 p.m. Additional hours may be necessary.