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Phd Statistics Jobs in Minnesota (NOW HIRING)

micro1 AI

Research Consultant - Physics AI

Rochester, MN · Remote

$80 - $140/hr

... 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 ...

micro1 AI

Physics Modeling Expert - Remote

Rochester, MN · Remote

$80 - $140/hr

... 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 ...

Team Velocity Marketing

Senior Data Scientist

Virginia, MN · On-site

$160 - $220/hr

Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field. Master's or PhD preferred. * 5+ years of experience building and deploying production ML ...

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Phd Statistics information

What is a PhD statistics?

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.

What are the key skills and qualifications needed to thrive in a PhD statistics position?

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.

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.

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, especially with specialized skills in statistical programming and data analysis tools.

Is a PhD in statistics worth it?

A PhD in statistics can lead to advanced roles in research, data analysis, and academia, often requiring strong analytical and programming skills in tools like R or Python. 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 I 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, quantitative analysts, research scientists, or statisticians, utilizing skills in statistical software, programming, and data interpretation. These roles typically require strong analytical abilities and knowledge of statistical methods and tools like R, Python, or SAS.

What are the most commonly searched types of Phd Statistics jobs in Minnesota?

The most popular types of Phd Statistics jobs in Minnesota are:

What are popular job titles related to Phd Statistics jobs in Minnesota?

For Phd Statistics jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Phd Statistics jobs in Minnesota look for?

The top searched job categories for Phd Statistics jobs in Minnesota are:

What cities in Minnesota are hiring for Phd Statistics jobs?

Cities in Minnesota with the most Phd Statistics job openings:

Phd Statistics jobs near you
Infographic showing various Phd Statistics job openings in Minnesota as of August 2026, with employment types broken down into 86% Full Time, and 14% Contract. Highlights an 43% In-person, 21% Hybrid, and 36% Remote job distribution.

Computational Physics Specialist - Remote

micro1 AI

Minneapolis, MN • Remote

$80 - $140/hr

Part-time

Posted 17 days ago

Job description

Role Title: Physics Expert (PhD / Postdoc)


Role Type: Contractor.


Location: Remote


micro1 is engaging Physics Experts (PhD / Postdoc) to contribute deep scientific knowledge and problem-solving skills to a high-impact customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Solve advanced physics problems from your specialization, delivering rigorous, well-documented derivations and analyses.
  2. Produce technically precise, clearly written solutions, detailing all assumptions, approximations, and final results using LaTeX mathematical notation.
  3. Utilize SymPy, Python, and Jupyter for symbolic or numerical verification and clear computational workflows where relevant.
  4. Identify and articulate subtleties in problem statements, including special cases, boundary conditions, and dimensional consistency.
  5. Flag ambiguities in project materials, proposing well-reasoned interpretations and clarifications as needed.
  6. Iterate on submitted solutions in response to feedback from project reviewers, ensuring corrections are cleanly integrated.
  7. Uphold rigorous standards in documentation and reproducibility consistent with professional research practice.


Preferred Qualifications

  1. PhD in physics or advanced-stage PhD candidacy, with active research experience in a relevant subfield.
  2. Research expertise in one or more of: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics, Condensed Matter (including moiré systems, magnetism, PXP/Rydberg), AMO/Quantum Optics, Gravitation, Cosmology, Astrophysics, Quantum Information, or Optical Properties of Materials.
  3. 2–5 recent representative publications (past ~5 years) in your field, with accessible arXiv or DOI records.
  4. Proficiency with LaTeX for presenting mathematics, and with SymPy, Python, and Jupyter for computational work; willingness to indicate areas for further support if needed.
  5. Demonstrated excellence in written technical communication, with a track record of producing clear, precise, and well-argued scientific outputs.
  6. Strong analytical skills, able to isolate key physical principles and provide nuanced solutions to complex problems.
  7. Availability to engage with the project consistently over an 8–10 week period (approx. 10 hours/week).

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