Overview:
The Data Scientist (Market Mix Modelling) plays a crucial role in analyzing market data to provide insights and recommendations that drive strategic business decisions. This role is essential for identifying the effectiveness of marketing strategies optimizing resource allocation and maximizing ROI.
Key Responsibilities:
- Conducting data analysis and modeling to understand market trends and customer behavior
- Developing and implementing market mix models to evaluate the impact of different marketing channels
- Collaborating with marketing and sales teams to identify key performance indicators and develop measurement frameworks
- Designing and executing A/B tests to assess the effectiveness of marketing campaigns
- Building predictive models to forecast market outcomes and marketing performance
- Applying statistical techniques to analyze large datasets and extract actionable insights
- Communicating findings and recommendations to stakeholders through reports and presentations
- Working closely with crossfunctional teams to integrate market mix models into business decisionmaking processes
- Staying updated with industry trends and best practices in market mix modeling and data science
- Contributing to the development and enhancement of data infrastructure and analytics tools
Required Qualifications:
- Masters degree or PhD in Statistics Mathematics Economics Computer Science or related field
- Proven experience in market mix modeling marketing analytics or related fields
- Proficiency in statistical analysis regression modeling and time series analysis
- Expertise in programming languages such as R or Python for data analysis and modeling
- Strong understanding of machine learning algorithms and techniques
- Ability to manipulate and analyze large complex datasets using SQL Hadoop or similar tools
- Excellent communication and presentation skills for conveying complex datadriven insights
- Experience with data visualization tools such as Tableau or Power BI
- Knowledge of marketing principles and concepts to interpret and contextualize modeling results
- Detailoriented approach with a focus on accuracy and reproducibility of results
- Proven ability to work effectively in a fastpaced dynamic environment and manage multiple priorities
- Strong problemsolving skills and a strategic mindset for leveraging data to address business challenges
- Experience in collaborative teamwork and crossfunctional project management
- Understanding of data privacy and compliance regulations in relation to market data analysis
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