Data Scientist – Merchandising & Inventory Machine Learning - Hybrid – Seattle, WA

As a Data Scientist in the Merchandising& InventoryMachine Learning team at Nordstrom, you will work on solving complex merchandisingand inventorychallenges using machine learning and optimization techniques to enhanceitem performanceand deliver exceptional customer experiences. Your focus will be on analyzing large datasets, building predictive models, and developing algorithms to support decision making in allfacetsof Nordstrom’s merchandising, such as demand forecasting,assortment,inventorypositioningand pricing optimization.

You will collaborate with cross-functional teams (other data scientists, software engineers, product teams, merchandising& inventorybusiness partners) to design, implement, and deploy innovative, robust, and scalable solutions. This is an excellent opportunity toleverageyour technical and communication skills, applycutting-edgemachine learning methods, and make a meaningful impact on Nordstrom’s operations and customer experience.

A day inthe life...

• Partner with product managers,engineersand other stakeholders to understand business problems andidentifyopportunities for machine learning applications tooptimizeitem lifecycle performance.

• Perform exploratory data analysis and statistical modelling to extract actionable insights from large and complex datasets

• Build andmaintainrobust data pipelines to process, clean and transform data from diverse sources (e.g.SQL datasets, APIs, flat files) 

• Design, develop and implement scalable and production-ready machine learning models / optimization algorithms for areas such as demand forecasting,assortment, and pricing optimization.

• Implement robust evaluation andmonitoringto validate the performance and reliability of machine learning models 

• Communicate complex findings,insightsand trade-offs to technical and non-technical stakeholders  

You own this if you have...

• Bachelor's, Master's, or PhD in Statistics,Data Science, Computer Science,Engineering,Operations Research,or a related technical field; or Equivalent related professional experience.

• Minimum1yearshands-on experience in Data Science or Machine Learning roles

• Minimum1years of professional SQL experience, performing advanced queries and optimization techniques

• Proficient coding skills in Python, with experience writing clean, maintainable, and optimized ML code 

• Experience applying statistical and machine learning algorithms, such as regression, decision trees, clustering, neural networks, survival analysis, along with model evaluation techniques

• A passion for solving complex problems with creative approaches.

• Strong communicationand collaboration skills, with the ability to work both independently and as part of a team 

Preferred Qualifications:

• Experience developing and deploying machine learning models in production environments

• Familiarity with machine learning libraries/frameworks such as Scikit-learn, TensorFlow,andPyTorch

• Curiosity to understand business processes andidentifyopportunities for innovation and improvement using data-driven approaches

• Exposure to cloud-based ML infrastructure and data pipelines (e.g., AWS, GCP, Azure)

• Knowledge and experience inretail 

• Motivation to stay current with advancements in data science and machine learning technologies

Core Competencies:

• Customer Focus: Commitment to deliveringa seamlesscustomer experience through technology solutions.

• Decision Quality: Ability to make sound decisions based on a mix of analysis, wisdom, experience, and judgment.

• Strategic Mindset: Capacity to take a long-term view andanticipatefuture trends and implications.

• Manages Complexity: Effectively navigates and simplifies complex situations and challenges.

• Communicates Effectively: Delivers clear, concise, and impactful messages to a variety of audiences.

• Drives Results:Demonstratesa strong drive to achieve meaningful outcomes.

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