E-Commerce Data Scientist

Z Supply

Costa Mesa, CA


Please apply directly to Z Supply for this role.

We are currently seeking a proficient and experienced Ecommerce Data Scientist with a deep understanding of the fashion and apparel industry and mastery in data science methodologies. This role will be critical in leveraging data to generate actionable insights that support key strategic decisions. This individual will particularly focus on areas such as customer retention, marketing performance, and product sales/returns, providing data-driven guidance to our ecommerce business.

Position Type: Full Time / Salary Exempt / $90,000 -$150,000 Annually

Reporting To: Director of Ecommerce

Location: Z SUPPLY Headquarters - Costa Mesa, CA

Work Type Hybrid Position - Partial In Office 3 Days / Partial Remote 2 days


  • Utilize data to derive actionable insights in areas such as customer retention, marketing campaign effectiveness, and product return rates.
  • Automate and streamline data analysis workflows to guide ecommerce business strategies.
  • Manage end-to-end data analysis tasks, including data extraction, cleaning, analysis, and interpretation.
  • Create intuitive dashboards and visualizations to communicate insights to relevant stakeholders.
  • Collaborate with cross-functional teams to align business objectives with data analysis.
  • Stay informed about the latest trends, technologies, and methodologies in the data science field and the fashion and apparel industry.


  • Bachelor's degree in Statistics, Computer Science, Mathematics, Economics, or related field
  • A minimum of 5 years of experience as an Ecommerce Data Analyst/Data Scientist , preferably within the fashion and apparel industry.
  • Expertise in statistical programming languages such as R or Python.
  • Experience with SQL and familiarity with database management. AWS or Shopify experience is a plus.
  • Proficiency with data visualization tools such as Tableau, PowerBI, Google Looker (Data Studio), etc.
  • Advanced understanding of data science methodologies, including but not limited to:
  • Data collection and cleaning: Experience with various data collection methodologies and the capacity to clean and standardize data for analysis.
  • Machine Learning: Ability to create predictive models using various machine learning techniques like regression, decision trees, random forests, and neural networks.
  • Statistical analysis: Capability to interpret and analyze data using statistical techniques and deliver ongoing reports.
  • Data mining: Knowledge of data mining techniques to extract significant insights from large datasets.
  • Predictive modeling and analytics: Experience with predictive models and analytics to anticipate trends and business outcomes.
  • Comprehensive understanding of ecommerce operations, customer retention strategies, marketing performance metrics, and product return analysis.
  • Exceptional communication skills with the ability to simplify complex data.
  • High attention to detail and accuracy.
  • Strong problem-solving skills and the ability to work independently.
  • Experience successfully scaling an enterprise-level ecommerce business.
  • Familiarity with A/B testing or experimental design.


  • Office / Desk Workstation
  • Air Conditioned
  • Computer / Laptop / Standard Office Equipment
  • Frequent use of hands with computers typing / dexterity
  • Occasional twisting while moving product / computer workstation


At Z SUPPLY, departments work cross-functionally enabling individuals to further their knowledge and expertise in an inclusive and supportive environment. In addition to a collaborative and supportive culture, here are a few additional perks that are enjoyed by the Z SUPPLY team:

  • Hybrid partial remote/in-office work schedule
  • Half-day Friday’s year round
  • Generous clothing discount
  • Comprehensive benefits package that includes medical, dental, and vision insurance coverage
  • 401K with discretionary annual company match
  • New chic and modern offices located near top restaurants and shopping.
  • Positive, collaborative company culture.
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