What are the responsibilities and job description for the Data Scientist II position at KOHLS?
About the Role
In this role 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
Lead exploratory data analysis to cull actionable insights
Collaborate with stakeholders to understand business requirements and translate them into technical solutions
Develop and implement statistical and machine learning models
Fine-tune, optimize and ensure the scalability of models and algorithms
Aid in designing experiments to answer targeted questions
Identify and drive continuous improvement of key business metrics in an assigned business functional area
Drive adoption and usage of data science products and models
Translate data science outputs into business outcomes and value delivered
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
PERSONALIZATION & RECOMMENDATION SYSTEMS
Accountabilities
Design and support deployment of machine learning models to power personalized experiences across digital channels (e.g., homepage, PDP, cart, campaigns)
Build and optimize recommendation and ranking systems balancing relevance, discovery, and business objectives (e.g., conversion, revenue)
Develop multi-stage ranking approaches, including candidate generation and re-ranking
Address cold-start and long-tail challenges in large product catalogs
Partner with engineering to support real-time personalization and scalable deployment
Skills & Experience
Experience with recommendation systems, search, or ranking problems at scale of millions of customers and products
Experience in developing sequential, transformer models and utilizing LLM models in production
Understanding of collaborative filtering and learning-to-rank methods
Experience optimizing models for GPU / distributed training
Familiarity with large-scale datasets and production ML systems
Exposure to real-time or low-latency serving environments
Experience with vector search / ANN methods (e.g., FAISS, ScaNN) preferred
Experience with delivering end to end customized ML models in production environment
Required
Bachelor’s Degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field
3 years of progressively complex data science experience
Extensive experience 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 to test the effectiveness of new strategies or initiatives and iterating quickly
Effective communication and collaboration skills at all levels
Preferred
Master’s degree and/or Ph.D.
Retail and Logistics experience
Supply chain management
Marketing models