招聘

Principal Product Manager - Inventory Intelligence (Hybrid - Seattle)
Seattle, WA
·
On-site
·
Full-time
·
Today
Job Description
Nordstrom's Inventory and Supply Chain team is seeking a highly technical product leader to drive the development of AI-powered optimization models and intelligent orchestration platforms that will transform how we manage inventory across our retail network. This role offers an exceptional opportunity to build mathematical optimization capabilities, agentic AI systems, and autonomous decision-making platforms that maximize inventory value while improving customer experience.
As the Principal Product Manager for AI-Powered Inventory Intelligence, you will work hands-on with data science and engineering teams to build production-grade optimization models for dynamic inventory positioning, develop AI agents that coordinate across specialized systems, and create the technical foundation for autonomous inventory management. You will be responsible for translating complex optimization problems into mathematical models, validating model performance through rigorous testing and backtesting, and architecting scalable AI systems that make real-time decisions across millions of SKUs and hundreds of locations.
This role is designed for a technical product leader with deep AI/ML expertise who can bridge advanced analytics and production engineering, collaborate directly with data scientists on model architecture, and drive transformational capabilities that represent significant business value for the enterprise.
A day in the life…
- Develop mathematical optimization models for inventory positioning decisions that maximize expected value by evaluating selling probability, inventory projections, capacity constraints, price trajectories, transportation times, and operational costs across our network
- Work hands-on with data scientists on model architecture, feature engineering, algorithm selection, and validation methodologies for production AI systems
- Build and validate optimization algorithms for dynamic allocation, replenishment, rebalancing, and recovery positioning including cross-banner returns and clearance inventory optimization
- Conduct backtesting, measure model performance using precision/recall/accuracy metrics, and iterate on model design to achieve business outcomes including cycle time reduction, improved recovery value, and margin optimization
- Make technical architecture decisions on optimization frameworks, data contracts, model integration patterns, and how AI agents coordinate to make autonomous decisions
- Partner with engineering teams to define technical requirements for real-time data pipelines, model serving infrastructure, and integration with warehouse management systems, transportation systems, and inventory platforms
- Design and validate A/B testing strategies to measure model impact on business metrics including inventory turns, recovery rates, in-stock improvement, and financial outcomes
- Build orchestration capabilities that coordinate specialized AI models (inventory placement, demand forecasting, performance optimization) to make holistic, autonomous inventory decisions
- Define model input requirements including demand forecasts, inventory projections, cost structures, capacity constraints, and business rules, working with data engineering teams to ensure data quality and availability
- Collaborate with cross-functional stakeholders in Supply Chain, Merchandising, Finance, and Operations to translate business requirements into technical optimization problems and validate model outputs against operational constraints
- Develop technical product roadmaps for AI-enabled inventory capabilities, balancing quick wins with long-term platform vision
- Lead technical discussions with data science teams on model selection (regression vs. classification vs. optimization), feature importance, hyperparameter tuning, and production deployment strategies
- Build trust mechanisms and explainability frameworks for AI recommendations to enable business users to understand and adopt model-driven decisions
- Define and track technical KPIs for model performance (latency, accuracy, precision, recall, business metrics) and establish monitoring and alerting for production AI systems
- Drive technical discovery and feasibility assessments for new AI use cases, evaluating build vs. buy decisions and determining technical approach for complex optimization problems
You own this if you have…
- 10+ years of product management experience with deep focus on AI/ML product development, mathematical optimization, or data science-driven products
- Proven track record of building and shipping production AI/ML systems at scale, working hands-on with data scientists on model development, validation, and deployment
- Strong technical background in mathematical optimization, operations research, machine learning, or related quantitative fields with ability to collaborate directly with data scientists on model architecture and algorithms
- Deep understanding of model validation methodologies including backtesting, A/B testing, precision/recall/accuracy metrics, and production model monitoring
- Experience with optimization problems in supply chain, inventory management, logistics, or similar domains involving resource allocation, routing, or positioning decisions
- Demonstrated ability to translate complex business problems into mathematical optimization frameworks and work with data science teams to develop and validate solutions
- Bachelor's degree in Computer Science, Data Science, Operations Research, Industrial Engineering, Mathematics, Statistics, or related quantitative field required; Master's or PhD preferred
- Hands-on experience with AI/ML concepts including feature engineering, model selection, hyperparameter tuning, and understanding of when to use different modeling approaches (regression, classification, optimization, reinforcement learning)
- Strong analytical skills with ability to work with large datasets, define data contracts, and ensure data quality for model inputs
- Proven ability to drive technical product strategy and roadmaps for AI-powered platforms, balancing short-term MVPs with long-term architectural vision
- Experience measuring business impact of AI/ML products through clear KPIs and demonstrating ROI to senior leadership
- Excellent technical communication skills with ability to explain complex optimization models and AI systems to non-technical business stakeholders and translate business requirements into technical specifications
- Demonstrated ability to influence and align senior stakeholders including VP and C-level executives on technical investment decisions and AI strategy
- Experience working in highly cross-functional, matrixed environments requiring collaboration across product, engineering, data science, and business teams
- Self-starter with strong ownership mentality and ability to drive results in ambiguous, greenfield problem spaces
- Familiarity with retail, supply chain, or inventory management systems preferred but not required - strong technical product leaders from other domains welcome
We’ve got you covered…
Our employees are our most important asset and that’s reflected in our benefits. Nordstrom is proud to offer a variety of benefits to support employees and their families, including:
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Medical/Vision, Dental, Retirement and Paid Time Away
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Life Insurance and Disability
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Merchandise Discount and EAP Resources
A few more important points...
The job posting highlights the most critical responsibilities and requirements of the job. It’s not all-inclusive. There may be additional duties, responsibilities and qualifications for this job.
For Los Angeles or San Francisco applicants: Nordstrom is required to inform you that we conduct background checks after conditional offer and consider qualified applicants with criminal histories in a manner consistent with legal requirements per Los Angeles, Cal. Muni. Code 189.04 and the San Francisco Fair Chance Ordinance. For additional state and location specific notices, please refer to the Legal Notices document within the FAQ section of the Nordstrom Careers site.
Applicants with disabilities who require assistance or accommodation should contact the nearest Nordstrom location, which can be identified at www.nordstrom.com.
Please be mindful that there may be legal notices and requirements related to this job posting that are specific to your state. Review the Career Site FAQ’s for relevant information and guidelines.
© 2022 Nordstrom, Inc
Current Nordstrom employees: To apply, log into Workday, click the Careers button and then click Find Jobs.
Nordstrom keeps job postings open for at least one day after the posting date.
Pay Range Details
The pay range(s) below has been provided in compliance with state specific laws. Pay ranges may be different for other locations.
Pay offers are dependent on the location, as well as job-related knowledge, skills, and experience.
$191,000.00 - $297,000.00 Annual
This position may be eligible for performance-based incentives/bonuses. Benefits include 401k, medical/vision/dental/life/disability insurance options, PTO accruals, Holidays, and more. Eligibility requirements may apply based on location, job level, classification, and length of employment. Learn more in the Nordstrom Benefits Overview by copying and pasting the following URL into your browser: https://careers.nordstrom.com/pdfs/Ben_Overview_17-19.pdf
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关于Nordstrom

Nordstrom
PublicNordstrom is an American luxury department store chain founded by John W. Nordstrom and Carl F. Wallin. The company operates full-line stores and Nordstrom Rack discount stores across the United States and Canada.
10,001+
员工数
Seattle
总部位置
$4.3B
企业估值
评价
3.9
10条评价
工作生活平衡
3.2
薪酬
3.8
企业文化
4.1
职业发展
2.8
管理层
3.4
72%
推荐给朋友
优点
Supportive management and team culture
Excellent benefits and employee discounts
Flexible scheduling
缺点
High-pressure sales environment and targets
Long hours during peak seasons
Limited advancement opportunities
薪资范围
43个数据点
L4
Senior/L5
Staff/L6
Director
L4 · TPM1 (Technical Program Manager)
1份报告
$130,000
年薪总额
基本工资
$120,000
股票
-
奖金
$12,000
面试经验
4次面试
难度
2.8
/ 5
时长
21-35周
录用率
25%
体验
正面 25%
中性 75%
负面 0%
面试流程
1
Application Review
2
Online Assessment
3
Recruiter Screen
4
Virtual/Phone Interview
5
Final Interview
6
Offer
常见问题
Behavioral/STAR
Coding/Algorithm
Technical Knowledge
Past Experience
Culture Fit
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