Data Scientist (P3860)

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

Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer-centric journey using 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing. 

Kroger Precision Marketing (KPM), powered by 84.51°, is the retail media arm of Kroger, helping brands build stronger connections with customers through data-driven insights and media activation. By combining Kroger’s loyalty data with the power of 84.51° data science and strategic media expertise, we provide brands with meaningful insights that fuel personalization and lead to impactful activations within the advertising ecosystem. Our comprehensive analytics bring customer stories and journeys to life—delivering measurable business impact for our brand partners while enhancing the customer experience. 

As a Data Scientist, you will support the AI Platform within KPM. In this role, you’ll be focused on foundational data science development to address strategic use cases across KPM’s commercial portfolio. You will collaborate with fellow data scientists, product managers, engineers, and AI enablement teams to prototype new methodologies, explore emerging technologies, and build scalable solutions that deliver measurable business value. 

To succeed in this role, you should be eager to learn and approach challenges with curiosity. You’ll need experience or familiarity with tools like Python, PySpark, SQL, Power BI or other similar statistical software to develop analytical solutions. Additionally, you’ll need familiarity with or a willingness to learn aspects of machine learning, statistical analysis, and modern AI frameworks. You should enjoy working in a team environment and be open to collaborating with data scientists, product managers, and business partners to support shared goals. 

Responsibilities 

• Assist with prototyping solutions and contributing to rapid decision-making in uncertain contexts. 

• Collaborate closely with cross-functional teams, including product, engineering, and business stakeholders, throughout discovery, prototyping, and scaling. 

• Have strong technical acumen and a passion around bringing new methodologies and capabilities to life to solve business problems 

• Support project execution by managing tasks effectively to ensure timely, high-quality delivery. 

• Interpret results and contribute to analysis and reporting for stakeholders. 

• Contribute to building scalable, high-quality code and pipelines with mentorship from senior teammates. 

• Identify gaps and opportunities in existing science, measurement, and data solutions, bringing forward ideas for team discussion. 

• Continuously challenge and improve 84.51°’s analytical capabilities and products. 

• Share knowledge, contribute to best practices, and build efficiencies as part of a collaborative data science community. 

Qualifications, Skills & Experience 

• A bachelor’s degree or higher in mathematics, statistics, computer science, data science, economics, or related discipline. 

• Demonstrated proficiency with components of our technology stack, such as Azure, Python, Spark, GitHub, Power BI, and Snowflake. 

• Experience working with databases, analyzing data, and presenting findings through academic projects, internships, or entry-level roles. 

• Strong analytical, problem-solving, and communication skills 

• Package building and code optimization experience or a strong desire to learn. 

• Ability to approach unstructured problems and develop clear, practical solutions with support from senior team members. 

• Ability to balance technical learning with business priorities to drive value. 

• Good organizational and time management skills, with the ability to handle multiple assignments. 

• Ability to collaborate effectively with cross-functional teams, including business stakeholders, product managers, and engineers 

• Natural curiosity and willingness to experiment and learn from mistakes. 

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