Staff Data Scientist (Remote)

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

Work arrangement
Yes