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For Companies At a Glance
- Tasks: Analyse marketing data to optimise campaigns and provide actionable insights.
- Company: Join Apple, a leader in innovation and technology, shaping the future of digital payments.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a dynamic team that values collaboration, creativity, and making an impact.
- Qualifications: Experience in data science, SQL, Python, and marketing analytics is essential.
- Other info: Work in a fast-paced environment with a culture of open feedback and rapid iteration.
The predicted salary is between 43200 - 72000 £ per year.
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 will be a thought partner to the marketing team, working closely with collaborators to understand their goals and critical metrics, and then analysing 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.
- Analyse 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
Marketing Data Scientist - Apple Pay employer: Apple Inc.
Contact Detail:
Apple Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Marketing Data Scientist - Apple Pay
✨Tip Number 1
Familiarise yourself with the latest trends in marketing analytics, especially around Apple Pay and similar financial products. Understanding the current landscape will help you engage in meaningful conversations during interviews.
✨Tip Number 2
Brush up on your SQL and Python skills, as these are crucial for the role. Consider working on personal projects or contributing to open-source projects that involve data analysis to showcase your abilities.
✨Tip Number 3
Prepare to discuss your experience with A/B testing and causal inference modelling. Be ready to share specific examples of how you've used these techniques to drive marketing decisions in past roles.
✨Tip Number 4
Network with professionals in the marketing analytics field, particularly those who have experience with Apple Pay or similar platforms. Engaging with industry experts can provide valuable insights and potentially lead to referrals.
We think you need these skills to ace Marketing Data Scientist - Apple Pay
Some tips for your application 🫡
Understand the Role: Before applying, make sure to thoroughly understand the responsibilities and qualifications required for the Marketing Data Scientist position at Apple Pay. Tailor your application to highlight how your skills and experiences align with their needs.
Highlight Relevant Experience: In your CV and cover letter, emphasise your experience with SQL, Python, and data visualisation tools like Tableau. Provide specific examples of how you've used these skills in previous roles, especially in marketing or analytics contexts.
Showcase Communication Skills: Since the role requires outstanding verbal and written communication skills, include examples in your application that demonstrate your ability to convey complex data insights to both technical and non-technical audiences.
Craft a Strong Cover Letter: Use your cover letter to express your passion for data science and marketing. Discuss how you can contribute to Apple Pay's marketing strategy and user experience, and mention any relevant projects or achievements that showcase your analytical capabilities.
How to prepare for a job interview at Apple Inc.
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with statistical modelling and causal inference analyses. Highlight specific projects where you used these skills to derive actionable insights, especially in marketing contexts.
✨Demonstrate Collaboration
Since the role involves working closely with marketers and business partners, share examples of how you've successfully collaborated across functions. Emphasise your ability to understand different goals and metrics while providing valuable insights.
✨Prepare for Technical Questions
Expect questions on SQL and Python, as well as your experience with data visualisation tools like Tableau. Brush up on your technical knowledge and be ready to discuss how you've used these tools in past roles.
✨Communicate Clearly
You’ll need to convey complex data findings to both technical and non-technical audiences. Practice explaining your analyses and results in simple terms, focusing on the implications for marketing strategy and user experience.
