Senior Data Scientist - Media Mix Modelling (MMM)

Key Responsibilities:

• Develop and implement Media Mix Models to optimize marketing spend across different channels (e.g., TV, digital, radio, print, etc.).
• Analyze historical data to understand the impact of marketing efforts and determine the effectiveness of different media channels.
• Collaborate with marketing and business teams to translate business objectives into quantitative analyses and actionable insights.
• Build predictive models to forecast the impact of future marketing activities and recommend budget allocation.
• Present and communicate complex findings in a clear, concise, and actionable manner to both technical and non-technical stakeholders.
• Perform deep-dive analyses of marketing campaigns and customer data to identify trends, opportunities, and areas for improvement.
• Ensure data integrity, accuracy, and consistency in all analyses and models.
• Stay up-to-date with the latest trends and advancements in media mix modeling, marketing analytics, and data science.
• Collaborate with cross-functional teams including Data Engineering, Marketing, and Business Intelligence to ensure seamless data flow and integration.
• Create and maintain documentation for all models, methodologies, and analysis processes.

Qualifications

• Bachelors or Masters degree in Data Science, Statistics, Economics, Mathematics, or a related field.
• Proven experience (4+ years) working in Media Mix Modeling (MMM) and/or marketing analytics.
• Strong proficiency in statistical modeling techniques (e.g., regression analysis, time-series modeling) and data analysis.
• Hands-on experience with tools and technologies such as Python, R, SQL, and data visualization platforms (e.g., Tableau, Power BI).
• Familiarity with marketing data sources (e.g., Nielsen, IRI, social media data, CRM, etc.).
• Excellent problem-solving skills and a strong analytical mindset.
• Ability to translate complex data into actionable insights and recommendations for business stakeholders.
• Strong communication skills with the ability to present findings to both technical and non-technical audiences.
• Experience working in a fast-paced, data-driven environment.
• Familiarity with machine learning techniques and frameworks is a plus.

Preferred Qualifications:

• Experience working with large datasets and cloud-based data platforms (e.g., AWS, Azure, Google Cloud).
• Knowledge of marketing attribution models, customer segmentation, and lifetime value (LTV) analysis.
• Experience in running A/B tests and controlled experiments.
• Prior experience in a consulting or marketing agency environment is a plus.