Manager, Data Science (Personalization & Recommendation Systems) (Remote)
Kohl’s, Inc.
Menomonee Falls, WI, United States
4 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source
Tech stack
Data Analysis
Big Data
Cloud Computing
Distributed Computing Environment
R (Programming Language)
Python (Programming Language)
Machine Learning
Recommender Systems
Search Technologies
SQL Databases
Google Cloud
Large Language Models
+5 more
Apache Spark
Information Technology
Machine Learning Operations
Tools for Reporting
Programming Languages
Job description
About the Role
As Manager, Data Science, you will manage a data science team and work with cross-functional partners to solve business challenges and promote data-driven decision-making with advanced data analysis and machine learning.
What You’ll Do
- Attract, retain, develop, manage, coach and assess data scientists in a balanced team
- Work with product, engineering and design leads and leverage data-driven insights to make decisions, set goals, prioritize work and achieve team objectives
- Lead end-to-end data science projects from problem formulation to model deployment, ensuring high-quality deliverables that meet business needs
- Oversee the design of experiments that answer targeted questions
- Identify and drive continuous improvement of key business metrics within assigned 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
- Remain current on the latest trends and developments in data science and technology and identify areas that offer the greatest return on investment
- 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 personalization & 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
- Expertise in developing and deploying state-of-the-art algorithms using machine learning and 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 such as Python, R, Spark, SQL, GCP, etc.
- Strong problem-solving skills with an emphasis on product development
- Experience proposing rapid experiments to test the efficacy of new strategies or initiatives and iterating quickly based on results
- Proven success guiding teams through unstructured technical problems
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or equivalent quantitative field
- 5+ years (or 2+ years with a Master’s degree) of progressively complex data science experience
- 2+ years of managerial or leadership experience in data science or analytics organizations
Preferred
- Master’s degree and/or Ph.D.
- Retail experience
- Marketing models
Requirements
- Experience with personalization & 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
- Expertise in developing and deploying state-of-the-art algorithms using machine learning and 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 such as Python, R, Spark, SQL, GCP, etc.
- Strong problem-solving skills with an emphasis on product development
- Experience proposing rapid experiments to test the efficacy of new strategies or initiatives and iterating quickly based on results
- Proven success guiding teams through unstructured technical problems
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or equivalent quantitative field
- 5+ years (or 2+ years with a Master’s degree) of progressively complex data science experience
- 2+ years of managerial or leadership experience in data science or analytics organizations
Preferred
- Master’s degree and/or Ph.D.
- Retail experience
- Marketing models
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