
10,000+ employees
Founded 1962
🛒 Retail
🛍️ eCommerce
👥 B2C
💰 $360M Post-IPO Debt - Kohl’s on 2025-05
Retail • eCommerce • B2C
Kohl's is a large U. S. omnichannel department store chain that operates nationwide brick-and-mortar stores and an online shopping platform, selling apparel, home goods, beauty products (including a Sephora at Kohl’s partnership), and other general merchandise. The company emphasizes customer-first retailing, inclusive workplace culture, and operates support functions such as distribution centers, credit and call centers, and design and corporate offices.
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10,000+ employees
Founded 1962
🛒 Retail
🛍️ eCommerce
👥 B2C
💰 $360M Post-IPO Debt - Kohl’s on 2025-05
Retail • eCommerce • B2C
Kohl's is a large U. S. omnichannel department store chain that operates nationwide brick-and-mortar stores and an online shopping platform, selling apparel, home goods, beauty products (including a Sephora at Kohl’s partnership), and other general merchandise. The company emphasizes customer-first retailing, inclusive workplace culture, and operates support functions such as distribution centers, credit and call centers, and design and corporate offices.
• Use data and insights to make decisions, set goals, and identify levers to achieve balanced team objectives • Lead end-to-end data science projects from problem formulation to model deployment • Oversee the design of experiments that answer targeted questions • Identify and drive continuous improvement of key business metrics • Translate data science outputs into business outcomes and delivered value • Maintain business partner relationships to gain cross-organizational alignment and drive adoption of data science capabilities • Mentor and guide junior data scientists • Stay current on data science and technology trends and identify implementation opportunities at Kohl’s • Develop prescriptive AI/ML solutions, including foundation models and predictive systems • Build quantitative evaluation harnesses for LLMs, SLMs, and multi-agent systems • Implement responsible-AI practices, bias detection, fairness constraints, data contracts, and model-risk controls • Integrate enterprise knowledge graphs and semantic layers for RAG pipelines and vector search/databases • Monitor production inference data for concept drift, data degradation, and model decay
• 6+ years of experience developing, evaluating, or applying modern AI/ML solutions, including LLMs, RAG, optimization, or causal methods, as relevant to the business problem • 6+ years of demonstrated understanding of AI evaluation, responsible-AI practices, and bias/risk mitigation • 6+ years of proven experience evaluating production GenAI and agentic systems using golden datasets, LLM-as-a-judge methodologies, guardrail hit rate analysis, and response failure analytics • Bachelor’s Degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field • 6+ years (or 3+ years with a Master’s degree) of progressively complex data science experience • Expertise in developing and deploying state-of-the-art algorithms using machine learning, statistical and optimization methods • Expert in using modern analytics tools, programming languages, and cloud platforms (Python, R, Spark, SQL, GCP, etc.) • Strong problem-solving skills with an emphasis on product development • Experience proposing rapid experiments and iterating quickly • Proven ability to guide teams through unstructured technical problems to deliver business impact • Preferred: Master's degree and/or Ph.D. • Preferred: Retail and Logistics experience • Preferred: Merchandising and/or Supply Chain Management • Preferred: Digital and/or Marketing models
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