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Staff Data Scientist (Remote)

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Remote

Staff Data Scientist (Remote)

Kohl's

Staff Data Scientist (Remote)

Skills

Google Cloud PlatformSQL QueriesPythonData ScienceRData AnalysisMachine LearningAISupply Chain ManagementSupply ChainRisk Management

18 days ago

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Important information


Contract type:

Permanent

Location:

Menomonee Falls, WI 53051, USA

Work mode:

Remote

Published on:

8 October 2026

What they need


About The Role As Staff Data Scientist, you will work with a data science team and cross-functional partners to solve business challenges and promote data-driven decision-making with advanced data analysis and machine learning.

What You’ll Do

  • Use data and insights to make decisions, set goals and identify the right 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 in the balanced team
  • Translate data science outputs into business outcomes and value delivered
  • Maintain strong business partner relationships to gain cross-organizational alignment, spur adoption and usage of data science capabilities and drive business outcomes
  • Mentor and guide junior data scientists, providing technical expertise and fostering a culture of continuous learning and development
  • Stay up to date on the latest trends and developments in data science and technology and identify implementation opportunities to support innovation at Kohl’s
  • Additional tasks may be assigned

Addendum

STAFF AI DATA SCIENTIST

  • Develop prescriptive AI/ML solutions - including foundation models and predictive systems - by converting complex business constraints into mathematical objective functions that guide optimal agent behavior.
  • Build and enforce continuous, quantitative evaluation harnesses to benchmark reasoning quality, tool-calling precision, grounding, and hallucination rates across LLMs, SLMs, and multi-agent swarms.
  • Implement rigorous responsible-AI practices across the model lifecycle, establishing proactive bias detection, fairness constraints, data contracts, and model-risk controls.
  • Partner with data and software engineering to integrate enterprise knowledge graphs and semantic layers, ensuring high-fidelity retrieval for retrieval augmented generation (RAG) pipelines and vector search/databases.
  • Oversee Day-2 telemetry in collaboration with domain teams to monitor production inference data, proactively detecting concept drift, data degradation, and model decay.

Requirements

  • 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.

Required What Skills You Have

  • 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 to power various aspects of highly complex business models and deliver value
  • 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 to test the effectiveness of new strategies or initiatives and iterating quickly
  • Proven ability to guide teams through unstructured technical problems to deliver business impact

Preferred

  • Master's degree and/or Ph.D.
  • Retail and Logistics experience
  • Merchandising and/or Supply Chain Management
  • Digital and/or Marketing models

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