Marketing Data Scientist - Apple Pay

London, England, United Kingdom Software and Services
Description The Data Scientist will play a key role in enabling insights for marketing campaign performance. This individual will provide measurement and campaign optimization insights for Apple Pay globally, which will inform and shape marketing strategy and user experience across the Apple Pay ecosystem. The successful candidate be a thought partner to the marketing team, will work closely with the collaborators to understand their goals and critical metrics, and then analyze data to provide actionable recommendations.Our culture is about getting things done iteratively and rapidly, with open feedback and discussion. We believe analytics is a team sport, but we strive for independent decision-making and taking smart risks.Data Scientist's day-to-day activities will include, but not be limited to:- Perform diagnostic analyses, including ML/statistical modeling and causal inference analyses, to quantify the lift of marketing campaigns.- Analyze marketing campaign performance across channels using sophisticated statistical and econometrics models to derive actionable insights.- Conduct descriptive analysis and deep dives in large-scale data to identify key insights and opportunities that will craft the future of marketing strategy and user experience.- Collaborate across functions with marketers and business partners to define hypotheses and success metrics.- Design and run experiments (A/B, multivariate) to evaluate new product features and marketing strategies, and use statistical methods to ensure valid and reliable results.- Supervise experiment performance, conduct interim analyses, and communicate findings clearly to technical and non-technical audiences.- Build data/model pipelines to automate recurring data pull and modeling processes.- Leverage Tableau and Keynote to visualise insights and deliver results in business presentations and dashboards.
Minimum Qualifications Relevant background in Strategy & Planning, Analytics, Data Science
Stakeholder Management: Outstanding verbal and written communication skills.
Strategic thinking and a consultative approach
Programming: Professional experience with SQL and Python.
Visualisation: Proven experience with Tableau for data visualisation and dashboard development
Prior professional experience in financial products and services
Strong experience in Business Analytics and Consulting
Preferred Qualifications Proven experience in marketing, advertising, or customer analytics
Data handling: Fluency with SQL queries in large and complex fragmented datasets and relational databases.
Statistics: Expertise in causal inference modeling and advanced statistical/ econometrics models, including regression and time series modeling.
Degree in Analytics, Data Science, Marketing or similar

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