Data Scientist, Apple Services Digital Marketing

Apple Apple · Big Tech · Culver City +1 · Marketing

Data scientist for Apple Services Digital Marketing team to analyze consumer feedback, optimize marketing and products, and monitor brand relevancy using statistics, ML, digital marketing data, and NLP.

What you'd actually do

  1. Build and maintain data driven optimization models, experiments, forecasting algorithms and machine learning models to better campaign performance, identify trends and optimize strategy.
  2. Provide causal analysis to evaluate the impact of various marketing initiatives, including both organic and paid placements.
  3. Design and continuously improve models that measure upper and mid-funnel marketing impact, integrating multiple metrics and diverse data sources in both structured and unstructured formats.
  4. Collaborate with cross-functional teams to propose solutions that address business problems.
  5. Assess business needs and translate model outputs into tangible and actionable insights and reports for both marketing and product teams.

Skills

Required

  • Bachelor’s degree with 3 years of experience in the data science field, or a Master’s degree in Data Science, Computer Science, or a related field with 2 years of experience.
  • Strong foundation in probability and statistics.
  • Proficiency in SQL and Python or R to work with large data sets.
  • Knowledge around supervised and unsupervised machine learning algorithms (regression, classification, clustering, decision trees, neural networks, etc).
  • Understanding of digital marketing data and KPIs, including Social, SEO, and Paid Media.
  • Ability to both solve problems with an analytical mind set and clearly explain findings and methodologies to technical and creative teams.

Nice to have

  • Familiarity with marketing measurement frameworks such as marketing mix modeling and attribution models.
  • Ability to partner and communicate effectively with cross-functional teams across marketing and engineering functions.
  • Proficiency in code collaboration /version control systems (e.g., Git, Github, GitLab).

What the JD emphasized

  • deep understanding of statistics
  • machine learning techniques
  • digital marketing data
  • NLP
  • actionable insights
  • successfully evangelize, educate, and enable

Other signals

  • optimize marketing and products
  • understand public consumer feedback at scale
  • monitor external brand relevancy