Description:

Join a global beauty brand in a dynamic, remote environment and drive data-driven decisions that shape customer experiences.
The company is a self-financed, female-owned beauty and lifestyle brand focused on making high-quality, eco-friendly hair accessories and beauty products accessible to everyone.
Founded in 2010, the brand has expanded from door-to-door sales to an international presence across 27 countries and 20,000 retail locations.
As a Data Analyst, you will enhance the brand’s operational efficiency and customer experience by analyzing logistics, website traffic, customer purchase behavior, and customer lifetime value (LTV).
Responsibilities include gathering and integrating data from multiple sources, ensuring data accuracy, optimizing operational workflows, performing analysis on customer behavior, and defining KPIs to communicate insights.

Requirements:

A Bachelor’s or Master’s degree in Data Science, Operations Research, or a related field is required.
Proven experience in e-commerce data analysis, specifically in website behavior, customer metrics, and logistics is necessary.
Experience with Shopify Plus and GA4 is required.
Experience with Daasity is also required.
Proficiency in Excel, GA4, CRM systems, and SQL is essential.
At least one programming language experience, either Python or Ruby, is required.
Strong SQL skills for data extraction and manipulation are necessary.
Strong problem-solving abilities with excellent attention to detail and the ability to translate raw data into actionable insights are required.
Ability to manage multiple projects independently and within a team, meeting deadlines and adapting to varied instruction sources is essential.

The position offers a fully remote work environment, allowing for flexibility and work-life balance.
You will be part of a dynamic team within a global beauty brand that values sustainability and inclusivity.
Opportunities for professional growth and development in a data-driven culture.
Engage in meaningful work that directly impacts customer experiences and operational efficiency.