Senior Data Scientist, Apple Ads
$150K - $277K/yr
Apply statistical, econometric, optimization, and causal inference techniques to better understand ... PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a ...
Senior Data Scientist, Apple Ads
$150K - $277K/yr
Apply statistical, econometric, optimization, and causal inference techniques to better understand ... PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a ...
Machine Learning Scientist III - Package Pricing
Austin, TX · On-site
$220K/yr
You will contribute to an area of active scientific research: causal inference, mixed integer ... Advanced degree (master's or PhD) in a quantitative discipline (e.g., Engineering, Statistics ...
Machine Learning Scientist III - Package Pricing
Austin, TX · On-site
$220K/yr
You will contribute to an area of active scientific research: causal inference, mixed integer ... Advanced degree (master's or PhD) in a quantitative discipline (e.g., Engineering, Statistics ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ... Past internship contributions include: Tensor-based complementary recommendations, published at ...
Causal Inference Phd Internship information
What types of projects does a causal inference PhD intern typically work on during their internship?
Causal Inference PhD interns often engage in projects that involve designing and analyzing experiments or observational studies to draw valid conclusions about cause-and-effect relationships. These projects might include developing statistical models, collaborating with data scientists and product teams, and presenting findings to inform business or policy decisions. Interns usually have the opportunity to work with large-scale, real-world data, and are encouraged to publish or present their work at conferences, supporting both professional growth and academic development.
What are the key skills and qualifications needed to thrive as a causal inference PhD intern, and why are they important?
To thrive as a Causal Inference PhD Intern, you need a strong background in statistics, econometrics, and causal inference methods, often supported by advanced graduate studies in a related field. Familiarity with statistical programming languages such as R or Python, and experience using data analysis tools and frameworks like Stata or TensorFlow Probability, are typically required. Excellent problem-solving abilities, critical thinking, and the ability to communicate complex concepts clearly help you stand out in this role. These skills and qualities are crucial for designing robust experiments, drawing reliable conclusions, and effectively collaborating with interdisciplinary research teams.
What is the difference between Causal Inference Phd Internship vs Data Scientist Internship?
| Aspect | Causal Inference Phd Internship | Data Scientist Internship |
|---|---|---|
| Required Credentials | PhD in statistics, economics, or related field | Bachelor's or Master's in CS, statistics, or related field |
| Work Environment | Research-focused, academic or industry research teams | Data analysis, modeling, and business insights |
| Employer & Industry Usage | Research institutions, tech companies, finance | Tech firms, startups, finance, healthcare |
| Search & Comparison Intent | Focus on causal inference research roles | Broader data analysis roles |
While a Causal Inference Phd Internship emphasizes research in causal analysis with advanced credentials, a Data Scientist Internship covers broader data analysis skills suitable for various industries. Both roles involve working with data, but their focus, required background, and career paths differ significantly.
What is a causal inference PhD internship?
A Causal Inference PhD Internship is a specialized research position for doctoral students focused on causal inference, which involves determining cause-and-effect relationships from data. Interns typically work with large datasets, advanced statistical models, and machine learning techniques to answer questions about how variables influence one another. These internships are often offered by tech companies, research labs, or policy organizations and provide hands-on experience in designing experiments, analyzing observational data, and developing new methodologies. The goal is to bridge academic research with real-world applications, contributing to projects that require rigorous causal analysis.
What are popular job titles related to Causal Inference Phd Internship jobs in Texas? For Causal Inference Phd Internship jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Causal Inference Phd Internship jobs in Texas look for? The top searched job categories for Causal Inference Phd Internship jobs in Texas are:
What cities in Texas are hiring for Causal Inference Phd Internship jobs? Cities in Texas with the most Causal Inference Phd Internship job openings:
$150K - $277K/yr
Full-time
Medical, Dental, Retirement
Re-posted 29 days ago
Apple rating
8.0
Based on 677 frontline employees who took The Breakroom Quiz
7th of 30 rated technology retailers
Job description
At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses.
Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes, from small app developers to global brands. Because when advertising is done right, it benefits everyone.
The Data Insights organization helps Apple Ads understand, measure, forecast, optimize, and improve the advertising ecosystem across Apple Services. We partner closely with Product, Engineering, Finance, Sales, and Leadership teams to solve complex business and product challenges using data, experimentation, statistical modeling, and machine learning.
We are hiring Data Scientists across multiple teams and areas of focus within Apple Ads. Successful candidates may be considered for a variety of opportunities depending on their experience, interests, and technical strengths. Our hiring process is designed to match candidates to the teams and problem spaces where they can have the greatest impact.
Description
As a Data Scientist within Data Insights, you will work on high-impact problems that influence product strategy, business performance, advertiser outcomes, and marketplace health across Apple's advertising platforms. Depending on your area of focus, you may contribute to one or more of the following domains:
- Product and Marketplace Insights: Define measurement frameworks, design experiments, evaluate product and advertiser outcomes, and identify marketplace opportunities that influence product strategy and decision-making.
- Business Insights: Own key business metrics, identify drivers of business performance, and translate analytical findings into actionable recommendations for leadership. Build scalable analytical frameworks and automation solutions that improve decision-making across the advertising ecosystem.
- Predictive Modeling, Forecasting & Optimization: Develop forecasting, machine learning, and optimization models that improve business performance and operational decision-making. Design robust evaluation frameworks and translate model outputs into scalable business impact.
- Advertiser GTM Research - Quantitative Research & Econometrics: Apply statistical, econometric, optimization, and causal inference techniques to better understand marketplace behavior, advertising effectiveness, and incrementality in support of strategic decision-making.
We hire across multiple levels and specialties within the Data Insights organization. Candidates may be considered for different teams and opportunities based on experience, interests, and business needs. Our goal is to match exceptional talent to the problems where they can create the greatest impact.","responsibilities":"Analyze large-scale datasets to identify opportunities, explain business outcomes, and influence decisions
Design and evaluate experiments to understand the impact of products, features, and marketplace changes
Develop statistical, machine learning, forecasting, optimization, or econometric models to solve business problems
Define metrics and measurement frameworks that improve visibility into product and business performance
Partner closely with Product, Engineering, Sales, Finance, Marketplace, and Leadership teams
Communicate analytical findings and recommendations to both technical and non-technical audiences
Translate ambiguous business questions into structured analytical approaches
Influence product, business, and strategic decisions through data-driven insights and recommendations
Contribute to a culture of analytical rigor, experimentation, and continuous learning
Preferred Qualifications
Masters or PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline and experience in one or more of the following areas:
Deep familiarity with experiment design and quasi-experimental frameworks
Experience applying causal inference methodologies and deriving insights from observational data at scale
Experience working on real-time bidding systems, advertising technology platforms, or attribution methodologies
Exposure to digital advertising, marketplaces, e-commerce, media, or consumer technology business related analysis
Forecasting and time series analysis, including revenue, supply, or demand forecasting
Building data products, analytical frameworks, or decision-support systems
Experience partnering with Product, Engineering, Sales, Finance, or executive leadership teams to drive business outcomes
Minimum Qualifications
Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline, or equivalent practical experience
Experience in Data Science, Analytics, Machine Learning, Quantitative Research, Business Analytics, or a related field
Strong SQL skills and experience working with large-scale, complex datasets
Strong Python programming skills and experience with common analytical libraries, including an understanding of code structure, testing, reproducibility, and scalable analytical workflows
Strong foundation in statistics, experimentation, causal inference, and analytical problem solving
Experience developing statistical, machine learning, econometric, forecasting, or optimization models to solve business problems
Experience translating analytical findings into business recommendations
Ability to communicate effectively with technical and non-technical stakeholders
Experience operating in ambiguous, fast-moving environments
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes, from small app developers to global brands. Because when advertising is done right, it benefits everyone.
The Data Insights organization helps Apple Ads understand, measure, forecast, optimize, and improve the advertising ecosystem across Apple Services. We partner closely with Product, Engineering, Finance, Sales, and Leadership teams to solve complex business and product challenges using data, experimentation, statistical modeling, and machine learning.
We are hiring Data Scientists across multiple teams and areas of focus within Apple Ads. Successful candidates may be considered for a variety of opportunities depending on their experience, interests, and technical strengths. Our hiring process is designed to match candidates to the teams and problem spaces where they can have the greatest impact.
Description
As a Data Scientist within Data Insights, you will work on high-impact problems that influence product strategy, business performance, advertiser outcomes, and marketplace health across Apple's advertising platforms. Depending on your area of focus, you may contribute to one or more of the following domains:
- Product and Marketplace Insights: Define measurement frameworks, design experiments, evaluate product and advertiser outcomes, and identify marketplace opportunities that influence product strategy and decision-making.
- Business Insights: Own key business metrics, identify drivers of business performance, and translate analytical findings into actionable recommendations for leadership. Build scalable analytical frameworks and automation solutions that improve decision-making across the advertising ecosystem.
- Predictive Modeling, Forecasting & Optimization: Develop forecasting, machine learning, and optimization models that improve business performance and operational decision-making. Design robust evaluation frameworks and translate model outputs into scalable business impact.
- Advertiser GTM Research - Quantitative Research & Econometrics: Apply statistical, econometric, optimization, and causal inference techniques to better understand marketplace behavior, advertising effectiveness, and incrementality in support of strategic decision-making.
We hire across multiple levels and specialties within the Data Insights organization. Candidates may be considered for different teams and opportunities based on experience, interests, and business needs. Our goal is to match exceptional talent to the problems where they can create the greatest impact.","responsibilities":"Analyze large-scale datasets to identify opportunities, explain business outcomes, and influence decisions
Design and evaluate experiments to understand the impact of products, features, and marketplace changes
Develop statistical, machine learning, forecasting, optimization, or econometric models to solve business problems
Define metrics and measurement frameworks that improve visibility into product and business performance
Partner closely with Product, Engineering, Sales, Finance, Marketplace, and Leadership teams
Communicate analytical findings and recommendations to both technical and non-technical audiences
Translate ambiguous business questions into structured analytical approaches
Influence product, business, and strategic decisions through data-driven insights and recommendations
Contribute to a culture of analytical rigor, experimentation, and continuous learning
Preferred Qualifications
Masters or PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline and experience in one or more of the following areas:
Deep familiarity with experiment design and quasi-experimental frameworks
Experience applying causal inference methodologies and deriving insights from observational data at scale
Experience working on real-time bidding systems, advertising technology platforms, or attribution methodologies
Exposure to digital advertising, marketplaces, e-commerce, media, or consumer technology business related analysis
Forecasting and time series analysis, including revenue, supply, or demand forecasting
Building data products, analytical frameworks, or decision-support systems
Experience partnering with Product, Engineering, Sales, Finance, or executive leadership teams to drive business outcomes
Minimum Qualifications
Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline, or equivalent practical experience
Experience in Data Science, Analytics, Machine Learning, Quantitative Research, Business Analytics, or a related field
Strong SQL skills and experience working with large-scale, complex datasets
Strong Python programming skills and experience with common analytical libraries, including an understanding of code structure, testing, reproducibility, and scalable analytical workflows
Strong foundation in statistics, experimentation, causal inference, and analytical problem solving
Experience developing statistical, machine learning, econometric, forecasting, or optimization models to solve business problems
Experience translating analytical findings into business recommendations
Ability to communicate effectively with technical and non-technical stakeholders
Experience operating in ambiguous, fast-moving environments
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
About Apple
Sourced by ZipRecruiter
Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Cupertino, CA, US
Year founded
1976