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Phd Causal Inference Jobs in Texas (NOW HIRING)

You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... PhD in related field Hands-on experience leveraging Generative AI to improve productivity and ...

You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... PhD in related field Hands-on experience leveraging Generative AI to improve productivity and ...

You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... PhD in related field Hands-on experience leveraging Generative AI to improve productivity and ...

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

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

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

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

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Showing results 1-20

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 Jul 23, 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 are the key skills and qualifications needed to thrive as a PhD Causal Inference researcher, and why are they important?

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 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 cities in Texas are hiring for Phd Causal Inference jobs? Cities in Texas with the most Phd Causal Inference job openings:
Applied Scientist

$175K - $308K/yr

Full-time

Medical, Dental, Retirement

Posted 19 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 673 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Services at Apple help hundreds of millions of customers get the most out of the devices they love through amazing apps, award-winning shows and movies, immersive music in spatial audio, world-class workouts and meditations, super fun games and more! The Services Data Science & Analytics organization is passionate about developing discerning insights and AIML solutions to help continually improve these services and accelerate growth while maintaining a strong dedication to customer privacy.
We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help optimize marketing channels, via observational testing frameworks, counterfactual modeling, and lifetime value estimation. As a key member of our diverse organization, you'll have the rare and rewarding opportunity to work with datasets of unique magnitude, richness, and dedication to privacy that will frequently require novel approaches. You'll work alongside partners across Business, Marketing, Product, Finance, and Engineering daily to deliver material customer and business value.
Description
As an Applied Scientist, you will have the responsibility of pushing the boundaries of how Causal Inference and AIML can be leveraged to better serve our customers. You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference solutions, that directly impact our products and provide a granular understanding of key marketing effectiveness. You will also be instrumental in defining the technical vision, strategy, and execution roadmap for our AIML initiatives, ensuring that we deliver high-quality, scalable, and impactful models that solve complex customer acquisition and engagement challenges. You will also be a key driver in fostering a vibrant culture of innovation, continuous learning, and collaborative problem-solving.","responsibilities":"Engineer end-to-end scalable and robust Causal Inference products which provide Apple with an understanding of the health of our Services’ marketing efforts.
Dive deep into large-scale data sources to uncover opportunities for Causal Inference automation, predictive methods, and quantitative modeling.
Collaborate with product managers, data scientists, and other engineering teams to translate business requirements into technical specifications and deliver impactful, practical solutions, increasing internal adoption of causal inference approaches and democratizing data
Stay abreast of the latest advancements in causal inference and AIML research, evaluating and integrating new frameworks where appropriate
Champion best practices in software engineering, MLOps, code quality, testing, documentation, and ensure compliance with data privacy and security
Preferred Qualifications
PhD in related field
Hands-on experience leveraging Generative AI to improve productivity and generate new insights
Curious business attitude with an ability to condense complex concepts and models into clear and concise takeaways that drive action
Minimum Qualifications
Master’s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field
3+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist role
Familiarity with a brand range of quasi-experimental Causal Inference techniques such as diff-in-diff, synthetic control method, panel analysis, regression discontinuity design, interrupted time series, and propensity score matching
Hands-on experience building Marketing Mix models and validation through Matched Market testing
Solid understanding of AIML technologies including Generative AI
Proven track record of successfully delivering complex projects from start to finish
Proficiency in programming languages such as Python, R, SQL, Java, or C++
Experience with cloud platforms, Spark, Docker, and MLOps tools and best practices
Excellent communication, collaboration, and presentation skills with meticulous attention to detail
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 $175,000 and $308,500, 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