01Key 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 (6+ 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.
Additional Information
What do you get in return
- Competitive Salary: Your skills and contributions are highly valued here, and we make sure your salary reflects that, rewarding you fairly for the knowledge and experience you bring to the table.
- Dynamic Career Growth: Our vibrant environment offers you the opportunity to grow rapidly, providing the right tools, mentorship, and experiences to fast-track your career.
- Idea Tanks: Innovation lives here. Our "Idea Tanks" are your playground to pitch, experiment, and collaborate on ideas that can shape the future.
- Growth Chats: Dive into our casual "Growth Chats" where you can learn from the best whether it's over lunch or during a laid-back session with peers, it's the perfect space to grow your skills.
- Snack Zone: Stay fueled and inspired! In our Snack Zone, you'll find a variety of snacks to keep your energy high and ideas flowing.
- Recognition & Rewards: We believe excellent work deserves to be recognized. Expect regular Hive-Fives, shoutouts and the chance to see your ideas come to life as part of our reward program.
- Fuel Your Growth Journey with Certifications: Were all about your growth groove! Level up your skills with our support as we cover the cost of your certifications. .
