Lead Audience Profiling

The Lead Audience Strategy & Profiling will drive advanced consumer profiling and multi-category audience strategies, combining strategic vision with deep technical expertise. This role is highly analytical and hands-on, leveraging SQL and Python to uncover patterns in consumer interactions, build predictive models, and deliver actionable insights that shape personalized consumer experiences across channels., Audience Strategy & Profiling

• Develop and refine audience segmentation frameworks for omni-channel activation.
• Translate consumer interaction data into actionable recommendations for CX design and personalization.
• Partner with brand, portfolio, and engagement teams to integrate audience strategies across the organization.

Advanced Analytics & Technical Execution

• Perform complex data analysis using SQL and Python to identify trends, clusters, and predictive behaviors.
• Build and maintain automated scripts, dashboards, and data pipelines for audience insights.
• Apply statistical and machine learning techniques to improve segmentation and targeting.

Campaign Measurement & Optimization

• Conduct pre- and post-campaign audience analytics to evaluate performance and refine strategies.
• Provide global recommendations based on learnings from completed campaigns.

Capability Building & Leadership

• Contribute to SOPs, OEBs, and toolkits to embed audience strategy in organizational processes.
• Mentor team members on technical best practices and advanced analytics.

Do you have experience in Tableau?, Do you have a Master's degree?, Education: Bachelor's or Master's in data science, Statistics, Marketing Analytics, or related field.

Experience required:

• 5+ years in audience strategy, profiling, or marketing analytics roles.
• Proven track record in hands-on data analysis and modeling.
• Excellent stakeholder management and ability to influence decisions.

Technical Expertise:

• Advanced proficiency in SQL and Python (data manipulation, modeling, automation).
• Experience with BI tools (Power BI, Tableau) and data visualization.
• Familiarity with cloud platforms and big data environments is a plus., * Experience with machine learning for segmentation and predictive modeling.
• Knowledge of CRM systems and consumer experience design.
• Understanding of GDPR and data privacy regulations.

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