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SKIMS

Product Manager, Data

Los Angeles, CA, United States

$165,000 to $180,000 USD / year

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Job details

Pay: $165,000 to $180,000 USD / year
Experience: 4+ years of experience in product management, technical product management, data and analytics, or a related field, including ownership of data or analytics products.
Posting language: English

Original job description

SKIMS is a solutions-oriented brand creating the next generation of underwear, loungewear, shapewear, and essentials. We are setting new standards by delivering technically innovative, comfort-driven products with elevated design for everybody.

At the intersection of culture, innovation, and commerce, SKIMS is a global brand redefining modern apparel. Our teams are built on creativity, collaboration, and operational excellence, and we are committed to fostering an inclusive, high-performance environment where ambitious, curious, and values-driven individuals can do the best work of their careers.

As we continue to scale globally, our HQ teams play a critical role in shaping strategy, building world-class infrastructure, and driving sustainable growth across markets.

SKIMS is seeking a Product Manager, Data to shape and deliver data products that make trusted, actionable information available across the business.

This role will translate business needs into a clear data product strategy, roadmap, and prioritized backlog. The Product Manager will focus on scalable, reusable capabilities rather than one-off reporting solutions, ensuring data investments support meaningful business decisions.

The ideal candidate combines product management discipline, technical fluency, and strong business judgment. They will partner closely with Data Engineering, Analytics, Data Science, and teams across Digital, Retail, Merchandising, Planning, Finance, Marketing, Operations, and Technology.

Key Responsibilities

Data Product Strategy and Roadmap

Define and maintain a data product roadmap aligned with SKIMS’ strategic and operational priorities.
Identify opportunities to create reusable data assets, standardized metrics, and self-service capabilities across business functions.
Prioritize investments based on business value, user needs, technical dependencies, and long-term scalability.
Define clear product outcomes, success measures, and decision criteria for roadmap initiatives.
Balance immediate stakeholder needs with sustainable platform and product development.

Product Discovery and Requirements

Partner with business stakeholders to understand workflows, decisions, pain points, and unmet data needs.
Translate ambiguous requests into product requirements, user stories, acceptance criteria, and clear definitions of success.
Facilitate alignment on business rules, metric definitions, source-system requirements, and intended user experiences.
Validate proposed solutions with users before and during development.
Communicate priorities, trade-offs, scope, and timelines clearly across technical and business teams.

Delivery and Product Lifecycle

Own the product backlog and partner with Data Engineering, Analytics, and other delivery teams to execute against the roadmap.
Coordinate dependencies across data sources, integrations, models, semantic layers, and reporting experiences.
Lead business validation, user acceptance testing, release readiness, and stakeholder enablement.
Monitor delivered capabilities and drive enhancements based on usage, feedback, and changing business needs.
Identify delivery risks early and support pragmatic decisions that protect product quality and value.

Data Quality, Governance and Trust

Champion consistent business definitions, clear ownership, documentation, and discoverability of data products.
Partner with technical teams to define expectations for data quality, reliability, freshness, and issue resolution.
Support scalable data models, governed metrics, and intuitive self-service analytics experiences.
Help reduce fragmented reporting and manual reconciliation through shared enterprise data capabilities.

Cross-Functional Partnership and Adoption

Build trusted relationships across Ecommerce, Retail, Merchandising, Planning, Finance, Marketing, and Operations.
Lead working sessions that connect business priorities to data product decisions and delivery plans.
Drive adoption through communication, training, documentation, and ongoing stakeholder feedback.
Measure product impact through usage, user satisfaction, reduced manual effort, and improved decision-making.
Promote a product-led, customer-focused approach to data across SKIMS.

Skills, Knowledge and Expertise

Qualifications

4+ years of experience in product management, technical product management, data and analytics, or a related field, including ownership of data or analytics products.
Experience defining product roadmaps, managing backlogs, and delivering cross-functional technical initiatives.
Strong understanding of data warehouses, pipelines, data modeling, business intelligence, and modern analytics workflows.
Working knowledge of SQL and the ability to independently explore data and validate business requirements.
Demonstrated ability to translate complex business needs into actionable technical specifications.
Experience with Agile delivery practices, user acceptance testing, and product management tools.
Excellent stakeholder management, facilitation, written communication, and presentation skills.
Strong analytical judgment and ability to prioritize competing needs in a fast-moving environment.
Bachelor’s degree in business, computer science, information systems, analytics, or a related field, or equivalent practical experience.

Preferred Qualifications

Experience within apparel, fashion, beauty, retail, ecommerce, or another consumer-facing business.
Familiarity with Snowflake, dbt, Looker, Fivetran, or comparable modern data technologies.
Experience with Shopify, NetSuite, ERP, merchandising, planning, or other enterprise source systems.
Understanding of omnichannel sales, customer, product, inventory, and marketing data domains.
Experience building governed metrics, semantic layers, master data capabilities, or self-service analytics products.
Exposure to data governance, data quality, forecasting, experimentation, or AI/ML-enabled products.

What Success Looks Like

Business and technical teams share a clear, prioritized roadmap for data products and capabilities.
High-value data initiatives are grounded in well-defined user needs and measurable outcomes.
Products are delivered reliably, validated with stakeholders, and adopted in day-to-day business workflows.
Core metrics and data products become more consistent, trusted, accessible, and reusable across teams.
Manual reporting and fragmented solutions decrease as scalable data capabilities mature.
Data investments enable faster, better-informed decisions and measurable business impact.

Benefits, Culture and Perks Benefits and Culture

Up to 100% Company Paid Healthcare (medical, dental, vision)
Kind Body Fertility Benefits
401(k) savings plan with up to 4% match
Unlimited PTO
Full Access to LinkedIn learning
Employee Discounts

Perks (HQ Location)

Free weekly catered lunch at HQ – M/T/W/Th
Dog-Friendly office on a Thursday and Friday
Free Swag Giveaways
Annual Holiday Party
Annual Summer Party
Invitations to pop-ups and other company events
Complimentary daily office snacks and beverages

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More about this job

Skills

Reporting
Data engineering
Merchandising
Product comprehension
Documentation
Data models
Communication skills
Decision making
Data modelling
Business intelligence
SQL
Agile
Stakeholder management
Presentation skills
Computer science
Snowflake
dbt
Looker
Shopify
Oracle NetSuite
ERP
Sales
Forecasting
ML

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