Senior Data Scientist, Apple Ads
$150K - $277K/yr
... causal inference, and analytical problem solving Experience developing statistical, machine learning, econometric, forecasting, or optimization models to solve business problems Experience ...
Senior Data Scientist, Apple Ads
$150K - $277K/yr
... causal inference, and analytical problem solving Experience developing statistical, machine learning, econometric, forecasting, or optimization models to solve business problems Experience ...
Senior Data Scientist, Apple Ads
$150K - $277K/yr
... causal inference, and analytical problem solving Experience developing statistical, machine learning, econometric, forecasting, or optimization models to solve business problems Experience ...
Senior Data Scientist, Apple Ads
$150K - $277K/yr
... causal inference, and analytical problem solving Experience developing statistical, machine learning, econometric, forecasting, or optimization models to solve business problems Experience ...
Senior Data Scientist
Plano, TX · On-site
Apply advanced machine learning, causal inference, and statistical techniques to optimize marketing strategies, campaign effectiveness, and customer experiences. * Build and test scalable data ...
Senior Data Scientist
Plano, TX · On-site
Apply advanced machine learning, causal inference, and statistical techniques to optimize marketing strategies, campaign effectiveness, and customer experiences. * Build and test scalable data ...
Senior Data Scientist
Plano, TX · On-site
Apply advanced machine learning, causal inference, and statistical techniques to optimize marketing strategies, campaign effectiveness, and customer experiences. * Build and test scalable data ...
Senior Data Scientist
Plano, TX · On-site
Apply advanced machine learning, causal inference, and statistical techniques to optimize marketing strategies, campaign effectiveness, and customer experiences. * Build and test scalable data ...
Apply advanced machine learning, causal inference, and statistical techniques to optimize marketing strategies, campaign effectiveness, and customer experiences. * Build and test scalable data ...
Apply advanced machine learning, causal inference, and statistical techniques to optimize marketing strategies, campaign effectiveness, and customer experiences. * Build and test scalable data ...
Leverage machine learning, causal inference methods or statistically sound analyses to drive actionable insights and help shape our understanding of marketing strategy, campaign planning, efficacy ...
Leverage machine learning, causal inference methods or statistically sound analyses to drive actionable insights and help shape our understanding of marketing strategy, campaign planning, efficacy ...
Senior Data Scientist, Apple Ads
$150K - $277K/yr
... causal inference, and analytical problem solving Experience developing statistical, machine learning, econometric, forecasting, or optimization models to solve business problems Experience ...
Senior Data Scientist, Apple Ads
$150K - $277K/yr
... causal inference, and analytical problem solving Experience developing statistical, machine learning, econometric, forecasting, or optimization models to solve business problems Experience ...
Data Scientist
Plano, TX · On-site
Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design * Experience in media performance analytics such as attribution modeling ...
Data Scientist
Plano, TX · On-site
Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design * Experience in media performance analytics such as attribution modeling ...
Senior Data Scientist
Plano, TX · On-site
Apply advanced machine learning, causal inference, and statistical techniques to optimize marketing strategies, campaign effectiveness, and customer experiences. * Build and test scalable data ...
Senior Data Scientist
Plano, TX · On-site
Apply advanced machine learning, causal inference, and statistical techniques to optimize marketing strategies, campaign effectiveness, and customer experiences. * Build and test scalable data ...
At the core of this is our Machine Learning and Inference Platform that powers the entire landscape. About the role In this role, you will architect, design, and lead the development of a SOTA ...
At the core of this is our Machine Learning and Inference Platform that powers the entire landscape. About the role In this role, you will architect, design, and lead the development of a SOTA ...
Data Scientist II
Crystal City, TX · On-site +1
Experimentation and causal inference Own A/B tests end-to-end, from design and power analysis ... Applied machine learning Use standard ML techniques (classification, regression, clustering) where ...
Data Scientist II
Crystal City, TX · On-site +1
Experimentation and causal inference Own A/B tests end-to-end, from design and power analysis ... Applied machine learning Use standard ML techniques (classification, regression, clustering) where ...
Job Title Postdoctoral Research Associate Agency Texas A&M Agrilife Research Department ... Strong training in applied econometrics, including causal inference methods. * Demonstrated ability ...
Job Title Postdoctoral Research Associate Agency Texas A&M Agrilife Research Department ... Strong training in applied econometrics, including causal inference methods. * Demonstrated ability ...
Optimize inference performance, model compression, and deployment across various hardware platforms ... Strong understanding of fundamental machine learning algorithms and neural network techniques.
Optimize inference performance, model compression, and deployment across various hardware platforms ... Strong understanding of fundamental machine learning algorithms and neural network techniques.
Principal Data Scientist
Austin, TX · On-site
$215K - $235K/yr
Strong background in statistics, forecasting, or causal inference. * Hands-on experience architecting machine learning solutions within cloud ecosystems. * Experience building, maintaining, and ...
Principal Data Scientist
Austin, TX · On-site
$215K - $235K/yr
Strong background in statistics, forecasting, or causal inference. * Hands-on experience architecting machine learning solutions within cloud ecosystems. * Experience building, maintaining, and ...
Job Title Postdoctoral Research Associate Agency Texas A&M Agrilife Research Department ... Strong training in applied econometrics, including causal inference methods. * Demonstrated ability ...
Job Title Postdoctoral Research Associate Agency Texas A&M Agrilife Research Department ... Strong training in applied econometrics, including causal inference methods. * Demonstrated ability ...
Machine Learning Engineer
Austin, TX · On-site
The role involves developing and optimizing machine learning models, managing large-scale datasets ... Optimize inference performance, model compression, and deployment across various hardware platforms ...
Machine Learning Engineer
Austin, TX · On-site
The role involves developing and optimizing machine learning models, managing large-scale datasets ... Optimize inference performance, model compression, and deployment across various hardware platforms ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
Gen AI Lead
Dallas, TX · On-site
$138K - $170K/yr
Machine learning development lifecycle - (Data preparation, Data visualization, Statistical ... AI, Causal Inference, Time series analysis, Forecasting, Anomaly detection, Hypothesis testing, A/B ...
Quick apply
Gen AI Lead
Dallas, TX · On-site
$138K - $170K/yr
Machine learning development lifecycle - (Data preparation, Data visualization, Statistical ... AI, Causal Inference, Time series analysis, Forecasting, Anomaly detection, Hypothesis testing, A/B ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
Causal Inference Machine Learning Postdoctoral information
What is a Causal Inference Machine Learning Postdoctoral researcher?
A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.
What are the key skills and qualifications needed to thrive as a Causal Inference Machine Learning Postdoctoral researcher, and why are they important?
To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.
What are some common challenges faced by Causal Inference Machine Learning Postdoctoral researchers when integrating causal models with real-world data?
Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.
What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?
| Aspect | Causal Inference Machine Learning Postdoctoral | Data Scientist |
|---|---|---|
| Required Credentials | PhD in statistics, machine learning, or related field | Bachelor's or Master's in data science, computer science, or related field |
| Work Environment | Academic research, research labs, universities | Corporate, tech companies, startups |
| Industry Usage | Research, academia, specialized industry projects | Business analytics, product development, data-driven decision making |
| Common Search/Comparison | Yes | Yes |
The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.
What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Texas? For Causal Inference Machine Learning Postdoctoral jobs in Texas, the most frequently searched job titles are:
- Mathematical Optimization Postdoc
- Remote Postdoctoral Medicinal Chemistry
- Postdoctoral Position Microbiology Bacteria
- Postdoctoral Materials Science
- Postdoc Biostatistics
- Postdoctoral Position Molecular Biology
- Temporary Postdoctoral Teaching Fellow
- Postdoc
- Remote Postdoctoral Teaching Fellow
- Postdoctoral Fellowship Physics
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Texas look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Texas are:
What cities in Texas are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities in Texas with the most Causal Inference Machine Learning Postdoctoral job openings:
$150K - $277K/yr
Full-time
Medical, Dental, Retirement
Re-posted 3 days ago
Apple rating
8.1
Based on 670 frontline employees who took The Breakroom Quiz
5th 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