Marketing Data Scientist

• Develop Data-Driven Insights: Utilize advanced data analysis techniques to extract actionable insights from large and diverse datasets across different European markets, driving strategic marketing decisions and commercial execution optimization. 

• Utilising ML methods (e.g supervised, unsupervised) on an Azure platform with languages such as Python, build and implement Predictive Models: Design, build, and deploy predictive and machine learning models to identify market trends, customer behaviour, and business process outcomes.  

• Analyze Multi-Channel Marketing Data: Integrate and analyze data from various marketing channels (e.g., transactional, firmographic, behavioral, digital data from advertising, social media, email campaigns) to assess performance, identify patterns, generate usable segmentations and recommend improvements to amplify future success of activities. 

• Collaborate with Cross-Functional Teams: Work closely with marketing, sales, and data teams to ensure alignment of data science initiatives with business goals. Enable analysts to further work on data points and reach data-driven recommendations to support in strategic planning and decision-making processes. 

• Ensure compliance to the Machine Learning Lifecycle from Data gathering through to Deployment. Appropriate checks and balances along with sufficient validation steps should be incorporated to maintain Data Quality and Compliance (e.g. GDPR and internal data governance policies) 

The ideal candidate would demonstrate: 

• Advanced Data Analysis and Modeling: Proficiency in statistical analysis and machine learning techniques, with experience in coding with Python, R, and SQL along with a good knowledge of Databricks is important. Knowledge of tools like Power BI for translating data into insights is a benefit. 

• Experience with Marketing Analytics: Strong background in analyzing and interpreting marketing data, with knowledge of marketing metrics, customer segmentation, and business performance evaluation. 

• Multi-Channel Data Integration: Expertise in integrating and analyzing data from various sources, including digital marketing platforms, CRM systems, large transactional databases, to create in depth intelligent views of customer cohorts. 

• Strong Communication Skills: Ability to clearly communicate complex data findings and insights to non-technical stakeholders, including creating detailed reports, visualizations, and presentations. 

• Cross-Cultural and Regional Awareness: Understanding of the nuances and variations in marketing practices and consumer behavior across different European markets, with the ability to adapt strategies to diverse regional needs.