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Phd In Statistics Jobs in Austin, TX (NOW HIRING)

... statistics, and machine learning to help optimize marketing channels, via observational testing ... PhD in related field Hands-on experience leveraging Generative AI to improve productivity and ...

Hardware Reliability Engineer

Austin, TX · On-site

$101K - $127K/yr

Experience in statistics and data analysis using one or more software/tools (e.g., MATLAB, Python, JMP, or Minitab). Preferred qualifications: * Master's degree or PhD in Hardware Engineering.

Biostatistician

Georgetown, TX · Remote

$60 - $65/hr

Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field. * Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or ...

Biostatistician

Round Rock, TX · Remote

$60 - $65/hr

Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field. * Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or ...

Biostatistician

Austin, TX · Remote

$60 - $65/hr

Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field. * Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or ...

Biostatistician

Georgetown, TX · Remote

$60 - $65/hr

Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field. * Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or ...

Biostatistician

Austin, TX · Remote

$60 - $65/hr

Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field. * Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or ...

Biostatistician

Round Rock, TX · Remote

$60 - $65/hr

Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field. * Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or ...

... stage PhD candidacy, with active research experience in a relevant subfield. * Research expertise in one or more of: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics ...

... stage PhD candidacy, with active research experience in a relevant subfield. * Research expertise in one or more of: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics ...

... stage PhD candidacy, with active research experience in a relevant subfield. * Research expertise in one or more of: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics ...

... stage PhD candidacy, with active research experience in a relevant subfield. * Research expertise in one or more of: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics ...

... stage PhD candidacy, with active research experience in a relevant subfield. * Research expertise in one or more of: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics ...

... stage PhD candidacy, with active research experience in a relevant subfield. * Research expertise in one or more of: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics ...

Data Center - MLB Reliability Engineer

Austin, TX · On-site

$101K - $127K/yr

... statistical concepts to non-experts. * Ability to manage multiple projects simultaneously in a fast-paced environment. Preferred Qualifications * MS or PhD in Reliability Engineering, Systems ...

Showing results 41-60

Phd In Statistics information

What is the difference between Phd In Statistics vs Data Scientist?

AspectPhd In StatisticsData Scientist
Required CredentialsTypically a PhD in Statistics or related fieldOften a bachelor's or master's degree in a quantitative field; some roles prefer a PhD
Work EnvironmentAcademic, research institutions, or specialized analytics teamsCorporate, tech companies, or consulting firms
Industry UsageResearch, academia, government, and industry R&DBusiness analytics, product development, and data-driven decision making
Common Search & ComparisonYesYes

While a Phd In Statistics focuses on advanced research, theoretical development, and academic roles, Data Scientists apply statistical and machine learning techniques to solve practical business problems. Both roles require strong analytical skills, but Data Scientists often work in more applied, industry-focused environments, whereas PhD holders may pursue research or academic careers.

Is a PhD in statistics worth it?

A PhD in statistics can lead to advanced roles in academia, research, data science, and analytics, often requiring strong analytical and programming skills. While it offers high-level expertise and potential for higher salaries, it also involves significant time and financial investment, and job prospects depend on industry demand and individual specialization.

What can you do with a PhD in statistics?

A PhD in statistics prepares individuals for advanced roles in data analysis, research, and modeling across industries such as healthcare, finance, technology, and government. Graduates often work as data scientists, statisticians, quantitative analysts, or research scientists, utilizing skills in statistical software, programming, and data interpretation to solve complex problems. These roles typically require strong analytical abilities and knowledge of statistical methods and tools like R, Python, or SAS.

What are popular job titles related to Phd In Statistics jobs in Austin, TX?

For Phd In Statistics jobs in Austin, TX, the most frequently searched job titles are:

Infographic showing various Phd In Statistics job openings in Austin, TX as of August 2026, with employment types broken down into 79% Full Time, 19% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution.
Apple
Computer and Electronic Product Manufacturing • 10K+ employees

$175K - $308K/yr

Full-time

Medical, Dental, Retirement

Re-posted 12 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 685 frontline employees who took The Breakroom Quiz


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.

What Apple employees say

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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