Senior Marketing Data Scientist
Apple
Senior Marketing Data Scientist
Job Description
At Apple, our Services help hundreds of millions of people get the most from the devices they love—whether through award-winning shows and movies, music in spatial audio, engaging workouts and meditations, amazing apps, or fun games. The Apple Media Products Data Science & Analytics team is dedicated to uncovering meaningful insights and building data-powered solutions that enhance our services and support business growth—while honoring Apple’s deep commitment to user privacy. We are seeking a Senior Marketing Data Scientist to help evolve our marketing strategies across Apple Services through the use of attribution, causal inference, testing, and predictive modeling. You’ll play a pivotal role in understanding and improving how we engage customers, working with large-scale data in collaboration with partners across Business, Marketing, Product, and Engineering. This is a unique opportunity to influence the future of marketing at Apple through innovative, customer-first approaches—and to do it in a supportive, growth-minded environment that values diverse perspectives and inclusive collaboration. Collaborate with cross-functional teams (Business, Engineering, Product, and Marketing) to define key metrics, data requirements, and models for analysis, experimentation, and reporting. Investigate large-scale datasets to identify trends, measure impact, and generate insights that improve marketing strategies. Develop attribution methodologies and frameworks to assess the effectiveness of campaigns across channels. Design and build datasets, reports, and dashboards to monitor campaign and channel performance at scale. Conduct ad-hoc analyses to support major initiatives and campaigns. Help shape marketing campaign touchpoints and customer journey strategies to deepen engagement. Build predictive models, including LTV and propensity models, to support campaign optimization and audience targeting. Evaluate the incremental impact of marketing efforts using causal inference and testing methodologies. Explore how emerging technologies, such as generative AI, can be applied to create business value. Communicate insights and strategic recommendations to Marketing, Business, Finance, and Executive stakeholders. Partner with teams across Apple to support responsible data collection, governance, and access.
Locations
- Culver City, California, United States 90232
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
50,000,000 - 90,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- attributionintermediate
- causal inferenceintermediate
- testingintermediate
- predictive modelingintermediate
- data analysisintermediate
- experimentationintermediate
- reportingintermediate
- investigating large-scale datasetsintermediate
- developing attribution methodologiesintermediate
- designing datasetsintermediate
- building reportsintermediate
- building dashboardsintermediate
- ad-hoc analysesintermediate
- shaping marketing campaign strategiesintermediate
- customer journey strategiesintermediate
- building predictive modelsintermediate
- LTV modelsintermediate
- propensity modelsintermediate
- campaign optimizationintermediate
- audience targetingintermediate
- evaluating incremental impactintermediate
- generative AIintermediate
- communicating insightsintermediate
- strategic recommendationsintermediate
- data governanceintermediate
- cross-functional collaborationintermediate
- inclusive collaborationintermediate
Required Qualifications
- 8+ years of experience as a Data Scientist or Analyst in marketing, media, subscription, or tech environments, with a proven track record of campaign measurement and optimization. (experience, 8 years)
- Strong proficiency in SQL and at least one programming language such as Python or R; experienced in building analytical datasets and pipelines using large-scale structured and unstructured data. (experience)
- Applied expertise in statistical and experimental techniques including A/B testing, regression, clustering, survival analysis, and causal inference. (experience)
- Demonstrated ability to translate complex data into clear, actionable business insights for cross-functional stakeholders. (experience)
- Bachelor’s degree in a quantitative field (e.g., Computer Science, Statistics, Economics) or equivalent professional experience. (experience)
Preferred Qualifications
- Experience in a digital subscription or large-scale e-commerce business (experience)
- Deep understanding of marketing effectiveness measurement, particularly through causal inference methods. (experience)
- Master’s or Ph.D. in a quantitative field is a plus, but not required. (degree in ph)
Responsibilities
- Collaborate with cross-functional teams (Business, Engineering, Product, and Marketing) to define key metrics, data requirements, and models for analysis, experimentation, and reporting.
- Investigate large-scale datasets to identify trends, measure impact, and generate insights that improve marketing strategies.
- Develop attribution methodologies and frameworks to assess the effectiveness of campaigns across channels.
- Design and build datasets, reports, and dashboards to monitor campaign and channel performance at scale.
- Conduct ad-hoc analyses to support major initiatives and campaigns.
- Help shape marketing campaign touchpoints and customer journey strategies to deepen engagement.
- Build predictive models, including LTV and propensity models, to support campaign optimization and audience targeting.
- Evaluate the incremental impact of marketing efforts using causal inference and testing methodologies.
- Explore how emerging technologies, such as generative AI, can be applied to create business value.
- Communicate insights and strategic recommendations to Marketing, Business, Finance, and Executive stakeholders.
- Partner with teams across Apple to support responsible data collection, governance, and access.
Tags & Categories
Senior Marketing Data Scientist
Apple
Senior Marketing Data Scientist
Job Description
At Apple, our Services help hundreds of millions of people get the most from the devices they love—whether through award-winning shows and movies, music in spatial audio, engaging workouts and meditations, amazing apps, or fun games. The Apple Media Products Data Science & Analytics team is dedicated to uncovering meaningful insights and building data-powered solutions that enhance our services and support business growth—while honoring Apple’s deep commitment to user privacy. We are seeking a Senior Marketing Data Scientist to help evolve our marketing strategies across Apple Services through the use of attribution, causal inference, testing, and predictive modeling. You’ll play a pivotal role in understanding and improving how we engage customers, working with large-scale data in collaboration with partners across Business, Marketing, Product, and Engineering. This is a unique opportunity to influence the future of marketing at Apple through innovative, customer-first approaches—and to do it in a supportive, growth-minded environment that values diverse perspectives and inclusive collaboration. Collaborate with cross-functional teams (Business, Engineering, Product, and Marketing) to define key metrics, data requirements, and models for analysis, experimentation, and reporting. Investigate large-scale datasets to identify trends, measure impact, and generate insights that improve marketing strategies. Develop attribution methodologies and frameworks to assess the effectiveness of campaigns across channels. Design and build datasets, reports, and dashboards to monitor campaign and channel performance at scale. Conduct ad-hoc analyses to support major initiatives and campaigns. Help shape marketing campaign touchpoints and customer journey strategies to deepen engagement. Build predictive models, including LTV and propensity models, to support campaign optimization and audience targeting. Evaluate the incremental impact of marketing efforts using causal inference and testing methodologies. Explore how emerging technologies, such as generative AI, can be applied to create business value. Communicate insights and strategic recommendations to Marketing, Business, Finance, and Executive stakeholders. Partner with teams across Apple to support responsible data collection, governance, and access.
Locations
- Culver City, California, United States 90232
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
50,000,000 - 90,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- attributionintermediate
- causal inferenceintermediate
- testingintermediate
- predictive modelingintermediate
- data analysisintermediate
- experimentationintermediate
- reportingintermediate
- investigating large-scale datasetsintermediate
- developing attribution methodologiesintermediate
- designing datasetsintermediate
- building reportsintermediate
- building dashboardsintermediate
- ad-hoc analysesintermediate
- shaping marketing campaign strategiesintermediate
- customer journey strategiesintermediate
- building predictive modelsintermediate
- LTV modelsintermediate
- propensity modelsintermediate
- campaign optimizationintermediate
- audience targetingintermediate
- evaluating incremental impactintermediate
- generative AIintermediate
- communicating insightsintermediate
- strategic recommendationsintermediate
- data governanceintermediate
- cross-functional collaborationintermediate
- inclusive collaborationintermediate
Required Qualifications
- 8+ years of experience as a Data Scientist or Analyst in marketing, media, subscription, or tech environments, with a proven track record of campaign measurement and optimization. (experience, 8 years)
- Strong proficiency in SQL and at least one programming language such as Python or R; experienced in building analytical datasets and pipelines using large-scale structured and unstructured data. (experience)
- Applied expertise in statistical and experimental techniques including A/B testing, regression, clustering, survival analysis, and causal inference. (experience)
- Demonstrated ability to translate complex data into clear, actionable business insights for cross-functional stakeholders. (experience)
- Bachelor’s degree in a quantitative field (e.g., Computer Science, Statistics, Economics) or equivalent professional experience. (experience)
Preferred Qualifications
- Experience in a digital subscription or large-scale e-commerce business (experience)
- Deep understanding of marketing effectiveness measurement, particularly through causal inference methods. (experience)
- Master’s or Ph.D. in a quantitative field is a plus, but not required. (degree in ph)
Responsibilities
- Collaborate with cross-functional teams (Business, Engineering, Product, and Marketing) to define key metrics, data requirements, and models for analysis, experimentation, and reporting.
- Investigate large-scale datasets to identify trends, measure impact, and generate insights that improve marketing strategies.
- Develop attribution methodologies and frameworks to assess the effectiveness of campaigns across channels.
- Design and build datasets, reports, and dashboards to monitor campaign and channel performance at scale.
- Conduct ad-hoc analyses to support major initiatives and campaigns.
- Help shape marketing campaign touchpoints and customer journey strategies to deepen engagement.
- Build predictive models, including LTV and propensity models, to support campaign optimization and audience targeting.
- Evaluate the incremental impact of marketing efforts using causal inference and testing methodologies.
- Explore how emerging technologies, such as generative AI, can be applied to create business value.
- Communicate insights and strategic recommendations to Marketing, Business, Finance, and Executive stakeholders.
- Partner with teams across Apple to support responsible data collection, governance, and access.
Tags & Categories