Data Analyst

About the role

The Data Analyst at CLO Virtual Fashion plays a central role in transforming how the company understands and optimizes digital apparel workflows. You will own the definition of critical product questions and the design of experiments that directly influence the evolution of virtual fashion. This position requires you to move beyond static reporting, actively shaping growth trajectories by converting complex style inquiries into actionable, structured datasets. You will serve as the primary translator between raw data and concrete decisions, ensuring that insights drive measurable changes in user behavior across the CLO ecosystem. A core part of your ownership involves building robust analysis frameworks that connect CLO-SET and CONNECT, clarifying how information cascades to decision makers and stakeholders. You will be accountable for reviewing dashboard logic to confirm that metrics accurately mirror business reality and the nuanced behaviors of virtual fitting sessions. Collaboration with offices across Asia, Europe, and the Americas will fall under your responsibility, as you align reporting structures to reflect distinct regional market patterns and preferences. Ultimately, you will trace event streams throughout the entire user journey, enabling rigorous hypothesis testing and documentation that secures the long term integrity of analytical assets.

Key facts

What you'll do

• Convert ambiguous style questions into clean, analysis ready datasets that feed directly into CLO and Marvelous Designer.
• Link product and business questions through structured analysis designs that clarify the relationship between CLO-SET workflows and CONNECT outputs.
• Validate dashboard logic against real user behavior and business outcomes, ensuring virtual fitting metrics reflect actual merchandising decisions.
• Produce concise guides that translate complex insights into concrete merchandising actions for teams across the product lifecycle.
• Coordinate with global teams based in Asia, Europe, and the Americas to synchronize reporting cycles and standardize key definitions.
• Design queries and event structures that enable rigorous hypothesis testing across the full user lifecycle from discovery to post purchase behavior.
• Create living documents that allow any teammate to understand core queries and independently reuse analytical logic without constant support.
• Measure the impact of minor data driven adjustments on style selections, identifying subtle patterns that influence user preferences.
• Review and refine data intake structures to ensure that raw style inquiries are transformed into high quality, usable datasets.
• Analyze the flow of production ready information between design tools to identify bottlenecks and opportunities for automation.
• Develop frameworks that connect virtual garment variants with real world merchandising constraints, improving planning accuracy.
• Monitor dashboard performance on an ongoing basis, recommending adjustments that keep metrics aligned with evolving business objectives.
• Lead cross functional discussions where data insights shape strategy for virtual fashion collections and seasonal planning.
• Document experimental results in a clear format that supports replication and learning across the organization.

Requirements

• Three to five years of dedicated experience analyzing product metrics within the context of digital fashion or related virtual goods.
• Strong SQL abilities essential for managing complex tables that track virtual garments, variants, and user interactions.
• Familiarity with how industry standard design tools pass production ready information between digital patterning and rendering systems.
• Clear English communication skills necessary for effective collaboration across multiple regions and time zones.
• Proven ability to work with structured and semi structured data in environments that blend creative and technical workflows.
• Comfort with fast paced environments where requirements evolve based on insights from live product testing.
• Experience translating business questions into testable hypotheses that can be validated through data.
• Commitment to maintaining high standards of documentation so that analytical work remains transparent and accessible.

Nice to have

• Background in virtual fashion workflows or 3D garment simulation, including hands on experience with platforms that digitize clothing design.

Practical notes

Please verify details on the official application page.

The hiring process at CLO Virtual Fashion is methodical and structured to assess both analytical rigor and collaborative fit. Applications move through a defined sequence beginning with document review, followed by a work sample test designed to evaluate practical data skills. Successful candidates then proceed to the first interview, which includes an English discussion and a live SQL test to gauge technical fluency. The second interview involves a deeper discussion with cross functional partners and may include reference checks to validate professional history. Compensation discussions occur after technical assessments to ensure clarity regarding expectations and scope. Candidates should anticipate multiple touchpoints before receiving a final offer, with each stage designed to align mutual goals and capabilities.

This role demands a disciplined approach to problem solving and a high level of ownership over analytical products. You will frequently interact with teams spread across Asia, Europe, and the Americas, requiring adaptability in communication style and work habits. The successful Data Analyst will thrive in an environment where data informs creative decisions, and where careful measurement of virtual fitting behaviors drives product innovation. Documentation and clarity are paramount, as your work will empower teammates to independently explore questions and validate hypotheses over time. By linking intricate digital workflows with concrete business questions, you will help CLO Virtual Fashion advance its mission of building a seamless digital fashion ecosystem.