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Phd Statistics Jobs (NOW HIRING)

GSK

ViiV Healthcare (GSK) Statistics Leader

Durham, NC · On-site

PhD in Statistics or a related quantitative field with at least 4 years post-degree experience or MS/MSc in Statistics (or related quantitative field) with 7+ years of clinical development experience

AbbVie

Manager - Statistics (Hybrid)

North Chicago, IL · On-site

$109K/yr

MS (with 6+ years of experience) or PhD (with 2+ years of experience) in Statistics, Biostatistics, or a highly related field. * Experience performing statistical computations and simulations

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$23.5K

$92.9K

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How much do phd statistics jobs pay per year?

As of Jul 5, 2026, the average yearly pay for phd statistics in the United States is $92,874.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,500.00 and $121,500.00 per year, depending on experience, location, and employer.

What can I do with PhD in statistics?

A PhD in statistics prepares individuals for advanced roles such as data scientist, quantitative researcher, biostatistician, or statistical consultant. Graduates often work in academia, government agencies, healthcare, finance, or technology sectors, utilizing skills in data analysis, modeling, and programming tools like R or Python.

What are the typical projects or research areas for someone with a PhD in Statistics?

A PhD in Statistics often works on projects involving the design and analysis of experiments, predictive modeling, advanced data analytics, and the development of new statistical methodologies. Depending on the industry, these may span sectors like healthcare, finance, technology, or government, requiring collaboration with diverse teams of subject matter experts. The role may also involve publishing research, presenting findings, and supporting organizational decision-making with evidence-based insights. This dynamic environment allows statisticians to solve real-world problems and continuously learn new analytical techniques.

Is getting a PhD in statistics worth it?

A PhD in statistics prepares individuals for advanced research, teaching, and data analysis roles that often require strong quantitative and programming skills. While it can lead to higher-level positions and increased earning potential, it also involves significant time and financial investment, and job prospects depend on industry demand and specialization.

What are the key skills and qualifications needed to thrive in the Phd Statistics position, and why are they important?

To thrive as a PhD in Statistics, you need advanced knowledge of statistical theory, data analysis, and research methodologies, typically backed by a doctorate in statistics or a closely related field. Expertise with statistical software such as R, SAS, Python, or MATLAB, along with experience in data management systems, is crucial. Strong problem-solving abilities, clear communication, and the capacity to work both independently and as part of interdisciplinary teams are highly valued soft skills. These qualities enable you to devise rigorous solutions to complex data challenges, effectively collaborate with colleagues, and translate findings for stakeholders.

Are statisticians highly paid?

Statisticians with a PhD often earn higher salaries due to advanced expertise and specialized skills in data analysis, modeling, and statistical software. Salaries vary by industry, experience, and location but generally tend to be above average compared to other roles in data-related fields.

How much does a PhD statistician make?

A PhD statistician typically earns between $80,000 and $150,000 annually, depending on experience, industry, and location. Senior roles or positions in finance, technology, or healthcare can offer higher salaries, often exceeding $150,000. Advanced skills in statistical software and data analysis increase earning potential.

What is a PhD Statistics job?

A PhD Statistics job typically involves conducting advanced statistical research, developing new methodologies, and applying statistical techniques to solve complex problems in various fields such as healthcare, finance, or technology. Professionals in these roles may work in academia, government, or industry, analyzing data, designing experiments, and publishing findings. They often collaborate with interdisciplinary teams to extract insights from large datasets and improve decision-making processes.

More about Phd Statistics jobs
What cities are hiring for Phd Statistics jobs? Cities with the most Phd Statistics job openings:
What are the most commonly searched types of Phd Statistics jobs? The most popular types of Phd Statistics jobs are:
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Phd Statistics jobs near you
Infographic showing various Phd Statistics job openings in the United States as of June 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 78% In-person, and 22% Remote job distribution, with an average salary of $92,874 per year, or $44.7 per hour.

Quantic - PhD Quantitative Researcher Intern (Summer 2027)

Walleye Capital Internships

Boston, MA • On-site

$20K/mo

Temporary, Internship

Posted 4 days ago

Job description

Position: Quantic - PhD Quantitative Researcher Intern (Summer 2027)
Location: Boston, MA
Please apply to only one opportunity between the Quantitative Developer, Quantitative Researcher and PhD Quantitative Researcher positions with Quantic. If the team finds you could be a potential fit for the other, we will contact you.
Firm Overview:
Walleye Capital is a ~$16 billion+ multi-strategy investment firm headquartered in New York City, with over 350 employees across five main offices. Founded in 2005 as an options market maker, we have organically grown into a global investment firm specializing in Quant, Fundamental Equities, and Volatility strategies.
Our Team Overview:
Walleye Capital is seeking highly quantitative and creative PhD Quantitative Researcher Interns to work in the rapidly growing Quantic team based out of Boston. Quantic is Walleye's principal quantitative investment business, established in 2016 as one of its core investment strategies. Quantic has subsequently evolved into one of the most successful trading teams in the industry.
We are a tight-knit, collaborative, and intellectually rigorous group of scientists, engineers, and traders leveraging advanced statistical modeling techniques to identify and capitalize on profitable trading opportunities in global equities, options, and futures. What sets Quantic apart is our pragmatic, engineering-driven culture, where achieving goals-and achieving them the right way-takes precedence. We foster collaboration among colleagues, confident that the best ideas arise through cross-disciplinary exchange. Our commitment to continuous self-reflection and growth drives us to build the strongest possible platform for our team's future success. We are seeking talented researchers to help elevate our capabilities and join us on this journey.
This role offers the opportunity to engage directly with cutting-edge data analysis, portfolio optimization, platform development, and operation of fully automated trading systems. You will join a team where your creativity, initiative, and teamwork will make direct impacts on trading profits for our investors. We invite researchers with a proven record of innovation and achievement in their fields to apply.
Position Overview:
As a Quantic Intern, you'll work directly with experienced team members on meaningful projects that impact trading strategies and operations. You'll have the opportunity to work on high-impact initiatives and develop your skills in a dynamic setting where innovation, teamwork, and talent drive success.
We are seeking students with strong technical backgrounds (e.g., mathematics, statistics, computer science, or engineering), demonstrated initiative, and an interest in quantitative trading and research. Successful interns are curious, collaborative, and eager to tackle complex problems in a fast-paced, supportive environment.
The internship is 10 weeks in length and will take place in Boston from June to August 2027.
Responsibilities:
  • Research, design, and test predictive signals, data sets, and systematic trading strategies.
  • Extract and analyze large datasets from structured and unstructured sources, applying advanced statistical and computational methods.
  • Enhance research infrastructure and tools for trading, risk management and attribution.
  • Develop machine learning models to predict patterns in asset returns, risks, trading costs, or other portfolio-relevant variables.
  • Design and implement scalable code across various stages of the investment process.
  • Work in Python and/or R, with opportunities to contribute to research tools and libraries.
  • Leverage AI tools including LLM-based analytical pipelines to enhance processes and analyses.

We seek individuals who:
  • Are pursuing a PhD degree in computer science, engineering, statistics, operations research, mathematics, or a related field, with an expected graduation date between December 2027 and June 2028.
  • Possess strong programming skills-particularly in Python or R-and hold experience working with large datasets, APIs, or databases.
  • Demonstrate rigorous analytical thinking, statistical modeling abilities, and familiarity with techniques from machine learning, optimization, or time-series analysis.
  • Are self-starters who enjoy digging into complex, open-ended problems and can work both independently and collaboratively with a team.
  • Exhibit a genuine interest in financial markets, systematic investing, AI/LLM application, and using technology in dynamic, data-rich environments.
  • Showcase creativity and enthusiasm for leveraging AI tools to enhance productivity, improve processes, and generate investment alpha.
  • Thrive in a collaborative culture that values intellectual humility, creativity, and continuous learning.

Pay Range:
The expected monthly pay for this position is $20,000/month. Interns will also receive a $10,000 housing stipend and transportation to and from Boston (domestic travel only).
The deadline to apply for this opportunity is Friday, October 30 at 11:59pm ET. For questions about the process, please review our Campus FAQs.
Please apply to only one opportunity between the Quantitative Developer, Quantitative Researcher and PhD Quantitative Researcher positions with Quantic. If the team finds you could be a potential fit for the other, we will contact you.
Walleye is an equal opportunity employer. Individuals seeking employment are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, sexual orientation, or any other category protected by applicable law.
If you require a reasonable accommodation to participate in any part of our hiring process, please contact HR@walleyecapital.com.
Personal data you provide will be processed in accordance with Walleye Capital LLC's Privacy Notice available at: https://www.walleyecapital.com/.

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