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Data Scientist (G1) P3438

Cincinnati, Chicago

SUMMARY:

We are a community of Data Scientists that work to improve the shopping experiences of our customers, both in-store and online. We leverage large volumes of data to develop powerful sciences using cutting edge machine learning, natural language processing, and mathematical techniques to improve products, processes, and systems that positively impact our customers. We lead our organization in identifying and adopting the tools and technologies that will continue to position our company as the recognized analytical leader within our industry.

The role is for a Data Scientist on the Enterprise Pricing & Promotions (EPP) team. EPP has a long-term focus to optimize pricing and promotion decisions at Kroger, including regular pricing, temporary price reductions, in-store promotional displays, weekly ad, and the various promotion tactics that our customers use to manage their grocery budgets. The role will directly support the development and deployment of analytical solutions Kroger uses to establish price and promotion strategies across grocery categories and geographic divisions to ensure it continues to be the leader in grocery retail.

RESPONSIBILITIES:

• Support the development and deployment of Pricing & Promotion solutions that leverage machine learning and advanced mathematical/statistical techniques
• Measure the efficacy of Pricing and Promotion strategies tested within the Kroger enterprise, as well as provide Kroger executive leaders with strong insights and direction for where and when the strategies should be scaled
• Develop data visualizations and dashboards using Power BI
• Engage with Kroger stakeholders to translate Pricing & Promotion problems into an executable analytic plan that supports Kroger decision making
• Integrate and combine transaction, cost, price, promotion, and competitive data into ad hoc solutions and mature products
• Ability to communicate how complex data, math, and statistics interact and impact Price and Promotion solutions to business and non-technical stakeholders

• Adhere to stringent quality assurance and documentation standards (Git/GitHub, Sphinx, Confluence)

• Stay up to date with progress made with academic and industry best practices

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• Bachelor’s degree or higher in mathematics, statistics, computer science, data science, business analysis, or related field
• Experience using advanced algorithms, programming languages, or technologies in the development of technical analytics solutions or capabilities
• Experience querying data from relational databases using SQL
• Experience using R, Python, or other similar statistical software
• Experience with data wrangling, data cleaning and prep, dimensionality reduction
• Data visualization skills and ability to present technical solutions to non-technical audience
• Exposure to Big Data concepts, tools, and architecture (e.g. Azure cloud, Spark, Hadoop)

• Strong analytical, creative problem-solving and decision-making skills

• Strong interpersonal and communication skills
• Natural curiosity that welcomes and embraces change and willingness to try new things and to fail
• Ability to work in a highly collaborative environment.