Data Scientist II (Remote)
Kohl's · Remote · Milwaukee
Job description
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
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Design and support deployment of machine learning models to power personalized experiences across digital channels (e.g., homepage, PDP, cart, campaigns)
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Build and optimize recommendation and ranking systems balancing relevance, discovery, and business objectives (e.g., conversion, revenue)
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Develop multi-stage ranking approaches, including candidate generation and re-ranking
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Address cold-start and long-tail challenges in large product catalogs
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Partner with engineering to support real-time personalization and scalable deployment Skills & Experience
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Experience with recommendation systems, search, or ranking problems at scale of millions of customers and products
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Experience in developing sequential, transformer models and utilizing LLM models in production
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Understanding of collaborative filtering and learning-to-rank methods
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Experience optimizing models for GPU / distributed training
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Familiarity with large-scale datasets and production ML systems
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Exposure to real-time or low-latency serving environments
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Experience with vector search / ANN methods (e.g., FAISS, ScaNN) preferred
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Experience with delivering end to end customized ML models in production environment Required
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Bachelor’s Degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field
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3+ years of progressively complex data science experience
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Extensive experience developing and deploying state-of-the-art algorithms using machine learning, statistical and optimization methods
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Expert in using modern analytics tools, programming languages, and cloud platforms (Python, R, Spark, SQL, GCP, etc.)
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Strong problem-solving skills with an emphasis on product development
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Experience proposing rapid experiments to test the effectiveness of new strategies or initiatives and iterating quickly
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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
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