SKIMS

Direct-to-consumer shapewear, underwear, loungewear

Product Manager - Data

Technical Product ManagementPosted on Nov 3

Full-timeLos Angeles, CA, USA$165k - $180k /yr

About the Job

Requirements

At least 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.
Strong stakeholder management and facilitation skills, with written communication and presentation abilities.
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.

Responsibilities

Define and maintain a data product roadmap aligned with 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.
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.
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.
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.
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.

Desired 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.

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.

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.

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.

About the Company

SKIMS

Direct-to-consumer shapewear, underwear, loungewear

SKIMS designs and makes underwear, shapewear, and loungewear aimed at a wide range of body types. Its products include bras, underwear, bodysuits, leggings, and loungewear sets, with emphasis on comfort and natural shaping. The company sells directly to consumers through skims.com, controlling brand experience and profit margins. The product line uses stretchable fabrics and technically constructed shapewear to provide support and shaping while remaining comfortable. SKIMS differentiates itself from competitors through inclusive sizing, body-positive branding, and a direct-to-consumer model that enables straightforward shopping and bundles that increase order value. The company’s goal is to set new standards in comfort-focused undergarments and apparel for diverse bodies and to expand its leadership in the shapewear and loungewear market.

Company size: 1,001-5,000
Company stage: Late Stage VC
Total funding: $894M
Headquarters: Los Angeles, CA
Founded: 2018

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