Data Analyst (Digital Marketing Analytics)

Permanent Employee, Full-time, Remote, PST Shift
Salary: ₱100,000 to ₱120,000

Job Summary:

We are seeking a Data Analyst with expertise in e-commerce, DTC, and retail analytics to extract, analyze, and visualize data that drives revenue and customer retention. This role requires strong skills in SQL, Python, and data visualization tools to develop reports, support predictive modeling, and optimize business strategies. The ideal candidate is highly analytical, proactive, and passionate about using data to inform business decisions.

Responsibilities:

  • Extract, clean, and structure data from multiple sources, including databases, APIs, and marketing analytics platforms.

  • Analyze customer behavior, sales trends, and campaign performance to generate actionable insights.

  • Develop, optimize, and maintain dashboards and reports to provide real-time business intelligence.

  • Collaborate with marketing, product, and merchandising teams to inform pricing, inventory planning, and customer segmentation.

  • Support the development of predictive models for demand forecasting, pricing optimization, and customer lifetime value analysis.

  • Conduct A/B testing and performance analysis to evaluate marketing campaigns, new product launches, and UX improvements.

  • Ensure data integrity and accuracy, proactively identifying and resolving inconsistencies.

  • Stay up to date with industry trends in data science, machine learning, and analytics to refine data strategies.

Requirements:

  • Proven experience in data analytics within e-commerce, DTC, or retail industries.

  • Expertise in SQL for complex queries, database management, and data warehousing.

  • Proficiency in Python for data analysis and automation.

  • Hands-on experience with data visualization tools such as Looker, Tableau, or Power BI.

  • Strong understanding of digital marketing analytics (Google Analytics, Meta Ads, TikTok Ads, Klaviyo, Shopify).

  • Familiarity with statistical modeling and forecasting techniques (e.g., regression analysis, clustering, predictive analytics).

  • Self-starter mindset with strong problem-solving skills—able to transform raw data into valuable insights.

  • Passion for the fashion industry and consumer behavior, with a keen understanding of shopping trends and online experiences.