Lead Data Scientist (P4318)

Summary

The SCORe team seeks a Lead Data Scientist to support Kroger Manufacturing with generative AI and data science solutions, including creating, managing, and monitoring agents, optimization, simulation, and machine learning. The ideal candidate will have a strong technical background in Generative AI, embeddings, NLP or statistical learning. Experience deploying in enterprise level manufacturing environments, especially food, and familiarity with 84.51°/manufacturing data assets is ideal.

 Responsibilities

Develop generative AI solutions to support manufacturing cost savings initiatives Integrate with and consult governance of contractor and third party owned sciences Integrate and deploy data science models to production grade front-end systems Apply MLOps best practices and patterns related to generative AI agentic workflows Develop and deliver analytical plans for client roadmaps, adopting best practices and innovative ideas. Transition projects from discovery to pre-production using the latest tech stack. Knowledge of Azure/Databricks platforms Experiment with innovative machine learning methods and conduct analytic experiments; share findings with the team. Scope and manage projects from start to finish, ensuring timely delivery within budget and specifications. Collaborate with stakeholders to design best-in-class solutions. Implement best practices for analysis, storage, and quality assurance with engineering, product, and labs teams. Identify opportunities for standardization and automation of solutions/processes. Develop actionable recommendations from data analysis to build relevant customer stories. Ensure high-quality work through quality assurance of your code and that of team members. Maintain documentation. Challenge and improve 84.51° analytic capabilities and best practices. Efficiently manage analytic resources to ensure timely delivery of business deliverables. Mentor data scientists to create standard processes and efficiencies; provide career development leadership for junior data scientists. Partner with G4 people leaders to prioritize work, identify risks and opportunities, and streamline team execution. Support building out the data science team to expand efforts Good knowledge of dataset development and maintenance.

 Qualifications, Skills, and Experience

Bachelor's degree in mathematics, statistics, analytics, data science, or a related discipline. 4+ years of experience in consulting or professional services, with at least 2 years focused on manufacturing. 4+ years of experience using advanced algorithms, programming languages, or technologies to develop technical analytics solutions. 4+ years of experience developing and implementing enterprise-scale generative AI solutions involving agentic workflows, NLP or embedding models Experience with graph databases and algorithms is a plus Proficiency in cleaning and querying data from relational databases and PySpark Experience using Python, or similar statistical software to develop analytical solutions. Expertise in data wrangling, data cleaning and preparation, and dimensionality reduction. Familiarity with Big Data concepts, tools, and architecture. Ability to create computationally efficient solutions. Strong academic background in mathematics, statistics, computer science, economics, or a similar discipline. Data visualization skills and the ability to present technical solutions to a non-technical audience. Strong analytical, creative problem-solving, and decision-making skills. Strong business acumen; manufacturing experience is a plus. Experience developing and implementing on cloud solutions (Azure, Databricks, etc.) Passionate about data, analysis, and insights. Natural curiosity that embraces change and a willingness to try new things and learn from failure. Ability to work in a highly collaborative environment

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