Lead Data Scientist (P3768)

84.51° Overview:

84.51° is a retail data science, insights and media company. We help the Kroger company, consumer packaged goods companies, agencies, publishers and affiliated partners create more personalized and valuable experiences for shoppers across the path to purchase.

Powered by cutting edge science, we leverage 1st party retail data from nearly 1 of 2 US households and 2BN+ transactions to fuel a more customer-centric journey utilizing 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

Join us at 84.51°!

Lead Data Scientist, Forecasting

The Forecasting Center of Excellence (FCOE) develops and manages multiple forecasts used by 84.51° and Kroger. Our main product is an item-level forecast used for price and promotion planning as well as supply chain operations for millions of items. This is a cross-functional team where data scientists, engineers, and product owners work collaboratively to support existing forecast sciences and deliver continuous product enhancements. The team leverages cutting-edge science and cloud technologies, working with big data assets in a cloud environment primarily with Python/Spark, generating billions of forecasts each day.

We are looking for a skilled and experienced data scientist who can apply forecasting algorithms to new problems and help support and improve existing forecast products. Our team is in the process of evaluating existing forecast models to determine their suitability in new business areas. We would especially be interested in someone with experience evaluating forecast models and helping identify and develop new features for those models. The ideal candidate will be able to program in Python and PySpark and be comfortable working with very large data sets (thousands of stores, millions of items, and billions of forecasts each day). There are ample opportunities to learn new skills and technologies and experiment with new forecast techniques or enhancements. Enthusiasm for learning, experimenting, and working with a highly-skilled, cross-functional team is key.

RESPONSIBILITIES:

• Assist in developing, deploying, and measuring new forecasts that can run in production environments to support mission-critical systems for millions of items.
• Steward and maintain existing forecast products, helping to improve these products and respond to user requests and questions by analyzing existing forecasts, identifying opportunities for improvement, and implementing those improvements in a continuous improvement process.
• Provide feedback and ideas to the FCOE Leadership Team to help direct the team's strategic roadmap and prioritization of new products and features.
• Develop and support forecasting tools, primarily using Python and Spark in an Azure/DataBricks environment.
• Deploying science solutions as automated jobs, science packages, or science as a service
• Document development work and forecast experiments, communicating results to the rest of the team.
• Serve as early adopter of new technology, helping to build out best practices and providing feedback to decision makers.
• Partner with a wide range of technical personas (i.e. engineering, architecture, research scientists) to deliver enhancements and collaboratively push 84.51°'s forecasting capabilities forward.

QUALIFICATIONS, SKILLS, AND EXPERIENCE :

• Bachelor's or Master's degree in data science, computer science, analytics, statistics, mathematics or related discipline
• 4+ years of experience in applied forecasting or machine learning
• 4+ years of experience working with and analyzing large data sets, summarizing results, and communicating results to team members and clients
• 4+ years of experience using advanced algorithms, programming languages, or technologies in the development of technical analytics solutions or capabilities.
• High level of independence, able to make time-sensitive decisions rapidly and solve urgent problems without escalation.
• Excellent communication skills, particularly on technical topics. Must be able to learn from others and teach others, and to work collaboratively as part of a highly-interdependent team.
• Strong Python skills, with some experience building large, modular applications or systems and science packages
• Comfort with independent learning of new technologies, and willingness to jump into using unfamiliar tools.
• Some experience with the following strongly preferred: PySpark, Databricks, Git, CI/CD tooling, Azure.
• Strong time and project management skills; the ability to balance multiple simultaneous work items and prioritize as necessary.

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