Description
Work Where You Matter: At Dollar General, our mission is Serving Others! We value each and every one of our employees. Whether you are looking to launch a new career in one of our many convenient Store locations, Distribution Centers, Store Support Center or with our Private Fleet Team, we are proud to provide a wide range of career opportunities. We are not just a retail company; we are a company that values the unique strengths and perspectives that each individual brings. Your difference truly makes a difference at Dollar General. How would you like to Serve? Join the Dollar General Journey and see how your career can thrive. Company Overview:
Dollar General Corporation has been delivering value to shoppers for more than 80 years. Dollar General helps shoppers Save time. Save money. Every day.® by offering products that are frequently used and replenished, such as food, snacks, health and beauty aids, cleaning supplies, basic apparel, housewares and seasonal items at everyday low prices in convenient neighborhood locations. Learn more about Dollar General at www.dollargeneral.com/about-us.html.
Job Details:This technical role within Decision Science & Analytics will support the Digital Team. This includes project work and insights and analytics primarily related to growing DG's Delivery/subscription program, as well as customer web and app behavior, digital engagement metrics, digital coupon and cashback usage, loyalty program (myDG), and other digital initiatives. This role will work collaboratively with the Digital team, as well as other key third parties, including internal IT resources and the broader Decision Science organization.
§ Become an expert in various sources of digital data and be able to use data to answer key business questions across initiatives using data, primarily using SQL and Python/PySpark. Translate projects and business questions into actionable insights and present findings, “telling the story” with data to non-technical stakeholders.
§ Understand sources, data frameworks and setup for existing and new reporting, particularly in PowerBI. Create automated, reusable analytics workflows from end-to-end: from developing and maintaining SQL/Python code to the final report or dashboard deliverable (PowerBI).
§ Gather and present insights related to digital behavior of the customer, including data gathering, analysis, visualization, and data-driven storytelling (PowerPoint presentations).
§ Develop dynamic, productionized, and scalable customer-level models for the Digital team based on their business needs
Qualifications:§ High level of experience in SQL, including writing and understanding complex queries and being able to use data and SQL to answer business questions
§ Intermediate to advanced skills with PowerBI, including setting up data frameworks for input into PowerBI
§ Experience developing code to combine, clean and prepare data for analyses and in some instances modeling using some combination of SQL, Python and PySpark (including but not limited to pandas, numpy, clustering, regression analysis)
§ Strong problem-solving skills utilizing expertise, business judgment and robust quantitative analyses
§ High-level written and verbal communication skills, as well as presentation (PowerPoint)
§ Demonstrated ability to translate complicated analytics topics and insights into easily communicable concepts to non-technical audience, including model accuracy and feature importance
§ Practical experience ingesting and manipulating large volumes of data (millions of records)
§ Proficiency with common analytical platforms, including distributed compute (e.g. Databricks, Snowflake, etc.)
§ Experience with code management tools such as Github (familiarity with CI/CD practices preferred). Experience with DBT a plus
§ Experience with retail industry or marketing and media networks is preferred
- MS in Data Science, Statistics, Economics, Computer Science, Mathematics, or related applied quantitative field preferred. Bachelor's in a highly quantitative/STEM field considered with the right experience.
- 2-5 years hands-on industry (non-academic) experience in Data Science or advanced Data Analytics (or equivalent quantitative job title).
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