Founded in 2011, Stylitics is an outfitting and styling technology partner to the world’s most forward-thinking retailers. We help retailers deepen customer relationships, maximize every sales opportunity, and create efficiencies everywhere from the design studio to the sales floor. An end-to-end outfitting solution that’s one part tech, one part brand strategy, and one part visual merchandising. Starting with a database of stylish outfit images that are created automatically according to your brand, Stylitics makes it possible for retailers to deliver personalized, outfit-driven experiences for every product, to every customer, everywhere—no stylist required.

As a senior product data analyst, you will leverage your skills in SQL, data engineering, and product planning to help us launch and measure our digital products. You will analyze consumer interaction data, manage A/B tests end-to-end, and build the data pipelines, dashboards, and presentations to help our product, engineering, and account teams know what works and what we should build next.

This role reports to the VP of Analytics and works day-to-day as part of a large, cross-functional team.

What You Will Do

• Partner with product, engineering, and account teams to ensure that we are tracking the right data to fully measure product success
• Help build data pipelines (using dashboarding and ETL tools) to summarize raw data into useful datasets and dashboards, in order to simplify and scale our analysis
• Define and document requirements for tracking user touchpoints with Stylitics products
• Contribute to ongoing and programmatic QA of data sources
• Build Looker dashboards and perform ad-hoc analyses to track product performance and evaluate hypotheses
• Enable opportunity evaluation – collaborating with product and finance stakeholders to collect data and build input-driven estimation tools

Must-Have Qualifications

• 5+ years of data analyst experience, with responsibility for initiating, executing, and presenting projects for cross-functional teams
• BS (or equivalent experience) in a technical field like Computer Science, Engineering, Mathematics, Statistics, or Marketing Analytics
• Fluent with complex SQL queries on millions of rows (joins, subqueries, window functions)
• Proficient understanding of how event data is tracked using tools like Google Analytics, Adobe Analytics, Snowplow Analytics, or Amplitude
• Experience with data visualization tools, like Looker, Tableau, or Power BI (we use Looker)
• Experience writing user stories and documentation for engineering teams
• Willingness to programmatically clean messy datasets (deduping, string parsing, JSON and XML parsing)
• Confidence to share the limitations of your analysis when the data isn’t perfect
• Advanced Excel proficiency (you should be comfortable with pivot tables and lookups to summarize results)

Nice-to-Have Qualifications

• Experience working with e-commerce and web data
• Experience with reproducible data analysis using Python or R
• Basic understanding of prediction and personalization algorithms (e.g. purchase and churn propensity models, product recommendations).
• This role will not build production models, but it will help if you understand how those models generally operate in connection to CRM and testing initiatives
• Experience setting up processes to monitor datasets for anomalies