Location: Los Angeles, CA (Hybrid - NOT remote eligible)
Salary: $225-250k base + bonus + equity
Company Overview:
A solutions-based apparel company that has experienced rapid growth and profitability since its founding in 2016. This direct-to-consumer e-commerce business is expanding into retail, with five stores currently open and plans for further growth. With over $1 billion in annual sales and 250-300 employees, the company partners with top-tier wholesalers and is driven by a mission to make customers feel their best.
Team Overview:
The Analytics team is expanding to support the growing business. Reporting to the SVP of Data, the Senior Director of Analytics will serve as the second-in-command, supporting senior stakeholders such as the SVP of Planning and VP of E-Commerce. The team currently consists of three Analysts, and additional hires are anticipated this year.
Role Overview:
As the Senior Director of Analytics, you will lead strategic initiatives that use data to drive decision-making and optimize business performance. You will tackle high-impact projects like demand forecasting, CLTV analysis, and retail store optimization. A strong understanding of how retail businesses operate, combined with the ability to apply data models in real-world scenarios, is essential.
Key Responsibilities:
Stakeholder Engagement: Collaborate with business leaders to develop data strategies that support company objectives.
Team Leadership: Mentor and develop a growing analytics team, fostering a high-performing, data-driven culture.
Hands-on Analytics: Lead key projects by writing SQL, performing statistical analysis, and presenting actionable insights.
Operationalize Data Solutions: Work with Data Engineering and Data Science teams to translate models into production-ready applications, enhancing business processes.
Key Projects:
Demand Forecasting: Address the challenge of aligning inventory with high customer demand.
Customer Behavior Analysis: Improve understanding of customer behavior to enhance CLTV and drive strategic decisions.
Retail Store Optimization: Analyze and optimize the performance of retail stores to improve efficiency and profitability.
Candidate Profile:
5-7 years of experience, including 2-3 years in a retail or fashion environment.
Experience applying data science models within retail/e-commerce.
Strong skills in SQL and proficiency in Python.
Proven experience with predictive and descriptive modeling.
Ability to translate complex data into clear insights for non-technical stakeholders, driving business impact.
A curious and proactive approach to working with vague datasets and uncovering actionable insights.