This technical role within Decision Science & Analytics will support the Digital Team. This includes project work and insights and analytics related to customer web and app behavior, including digital engagement metrics, digital coupon and cashback usage, loyalty program (myDG) enrollment, 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.
Job Responsibility 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. (50%) 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). (30%) Gather and present insights related to digital behavior of the customer, including data gathering, analysis, visualization, and data-driven storytelling (PowerPoint presentations). (15%) Develop dynamic, productionized, and scalable customer-level models for the Digital team based on their business needs. (5%)
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- Job 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.
Education/Experience
- 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 equivalent quantitative job title).
