Omnichannel Marketing Analyst

Job responsibilities

• Help work on market research, segmentation and social listening analysis to understand the latest beauty trends, media consumptions, and consumer behaviors.
• Execute analysis of marketing campaigns and strategic initiatives across key channels; evaluate performance metrics, creative outputs, cross-channel activation, and consumer trends to surface insights and support recommendations.
• Deliver monthly reports on customer behavior, social performance, and the competitive landscape, incorporating financial data to support decision-making.
• Regularly monitor key KPIs to track performance shifts and inform optimization.
• Support the design of measurement frameworks to assess brand impact and marketing effectiveness, including testing strategies, learning agendas, and benchmarks.
• Build and maintain scalable self-service dashboards; partner with technical teams to automate reporting and ensure data accuracy.
• Translate data into clear insights and key findings to support recommendations and stakeholder decision-making.
• Support data collection, validation, and QA to ensure accurate, reliable reporting.
• Leverage tools (e.g., BigQuery) to build automated, scalable data processes and anomaly detection.
• Maintain data structures and categorization for consistent analysis.
• Support cross-functional analytical initiatives by coordinating timelines, aligning inputs across teams, and tracking deliverables.
• Keep teams updated on current digital, consumer, and analytics trends.

Profile

• Bachelor's degree in Marketing, Analytics, Statistics, Mathematics, Business, or related fields. Equivalent experience may be accepted.
• 2-3 years in data analysis, customer insights, research, or business intelligence, specifically in marketing analytics.
• Strong proficiency in Excel, including pivot tables and advanced functions.
• Experienced with qualitative analysis; familiarity with statistical modeling and A/B testing a bonus.
• Working knowledge of data modeling, data structures, and data warehousing.
• Experience with data visualization tools (e.g., Power BI, Tableau).
• Experience working with cross-functional teams in a collaborative environment.
• Experience in retail/wholesale data preferred; beauty industry experience a strong plus