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Phd Causal Inference Jobs in Texas (NOW HIRING)

Senior Data Scientist, Apple Ads

Austin, TX

$150K - $277K/yr

  • Medical

  • Dental

  • Retirement

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

Austin, TX

$150K - $277K/yr

  • Medical

  • Dental

  • Retirement

Apply statistical, econometric, optimization, and causal inference techniques to better understand ... PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a ...

Staff Data Scientist

Austin, TX

  • Medical

  • Dental

  • Vision

  • Retirement

Advanced degree (Master's or PhD) in a quantitative field such as computer engineering ... Strong background in statistics, forecasting, or causal inference.  * Hands-on experience ...

Staff Data Scientist

Austin, TX · On-site

$145K - $205K/yr

Advanced degree (Master's or PhD) in a quantitative field such as computer engineering, statistics ... Strong background in statistics, forecasting, or causal inference. * Hands-on experience ...

Showing results 21-40

Phd Causal Inference information

See Texas salary details

$37.3K

$114.5K

$166.3K

How much do phd causal inference jobs pay per year?

As of Aug 18, 2026, the average yearly pay for phd causal inference in Texas is $114,527.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,800.00 and $128,600.00 per year, depending on experience, location, and employer.

What is a PhD in causal inference?

A PhD in Causal Inference is an advanced research degree focused on understanding and identifying cause-and-effect relationships using statistical and computational methods. Students in this field learn to design studies, analyze data, and develop new methodologies to answer complex causal questions in areas such as social sciences, medicine, economics, and artificial intelligence. Graduates often work in academia, research institutions, or industries where evidence-based decision-making is essential.

What are the key skills and qualifications needed to thrive as a PhD causal inference researcher?

To thrive as a PhD Causal Inference researcher, you need advanced knowledge of statistics, econometrics, and causal modeling, typically supported by a doctoral degree in a quantitative field. Familiarity with statistical programming languages (such as R or Python), specialized software (like STATA or SAS), and experience with experimental or quasi-experimental methods are essential. Strong analytical thinking, attention to detail, and the ability to communicate complex findings clearly make a candidate stand out. These skills ensure rigorous, credible research that can inform policy, product development, or scientific understanding by accurately identifying causal relationships.

What collaborative opportunities can a PhD specializing in causal inference expect within a multidisciplinary research team?

PhD professionals in Causal Inference frequently collaborate with experts from fields such as epidemiology, economics, computer science, and public health. They often work closely with data scientists, subject matter experts, and statisticians to design studies, interpret complex datasets, and develop robust analytical models. This multidisciplinary environment fosters continuous learning and often leads to co-authorship on research publications, participation in grant writing, and involvement in high-impact policy or product decisions. Effective communication and teamwork skills are essential to translate technical findings for diverse audiences and drive actionable insights.

What cities in Texas are hiring for Phd Causal Inference jobs?

Cities in Texas with the most Phd Causal Inference job openings:

Senior Data Scientist, Apple Ads

Apple

Austin, TX

$150K - $277K/yr

Full-time

Medical, Dental, Retirement

Re-posted 7 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

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.

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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