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Phd In Statistics Jobs in Springfield, MA (NOW HIRING)

PhD in physics and an active record of independent research within a specialized subfield (e.g., High Energy/Mathematical Physics, Biophysics/Statistical Physics, Condensed Matter, AMO/Quantum Optics ...

Biostatistician

Springfield, MA · Remote

$60 - $100/hr

MS or PhD in biostatistics, statistics, or epidemiology. * 4+ years of experience in pharmaceutical, contract research, hospital, or academic medical contexts. * Demonstrated command of clinical ...

MS or PhD in biostatistics, statistics, or epidemiology. * 4+ years of experience in pharmaceutical, contract research, hospital, or academic medical contexts. * Demonstrated command of clinical ...

PhD in physics and an active record of independent research within a specialized subfield (e.g., High Energy/Mathematical Physics, Biophysics/Statistical Physics, Condensed Matter, AMO/Quantum Optics ...

Biostatistician

Hartford, CT · Remote

$60 - $100/hr

MS or PhD in biostatistics, statistics, or epidemiology. * 4+ years of experience in pharmaceutical, contract research, hospital, or academic medical contexts. * Demonstrated command of clinical ...

PhD in Mathematics, Statistics, Engineering, or other STEM fields preferred with 4-6 years of experience in insurance industry or related industry in a data science, analytics, or AI environment.

Master's or PhD in a quantitative field such as Data Science, Statistics, Computer Science, or similar. * Experience with GenAI and LLM technologies such as GPT, RAG, or vector databases.

Showing results 21-40

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.

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, quantitative analysts, research scientists, or statisticians, 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.

Is a PhD in statistics worth it?

A PhD in statistics can lead to advanced roles in research, data science, and academia, 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.

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Infographic showing various Phd In Statistics job openings in Springfield, MA as of August 2026, with employment types broken down into 81% Full Time, 16% Part Time, 1% Temporary, and 2% Contract. Highlights an 74% Physical, 2% Hybrid, and 24% Remote job distribution.

AI Training Specialist - Physics

micro1 AI

Hartford, CT • On-site, Remote

$80 - $150/hr

Part-time

Posted 12 days ago


Job description

Role Title: Physics Expert (Postdoc / Junior professor)


Role Type: Contractor


Location: Remote (US, Canada, UK focused)


micro1 is engaging Physics Experts (Postdoc / Junior professor) to participate in a high-impact project supporting a customer in the science and technology sector. 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. Critically evaluate and review physics solutions, mathematical derivations, and theoretical arguments generated by researchers or AI platforms.
  2. Detect errors, unjustified steps, missing assumptions, dimensional inconsistencies, and weaknesses in logic or methodology.
  3. Delineate between substantive scientific issues and stylistic or cosmetic matters, providing technically precise written feedback.
  4. Articulate and document the reasoning behind any identified flaws, ensuring actionable guidance for improvement.
  5. Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the argument.
  6. Utilize LaTeX, SymPy, Python, and Jupyter to independently verify or counter-check scientific claims as appropriate.
  7. Deliver structured feedback designed to support iterative enhancement of submitted work and project outcomes.


Preferred Qualifications

  1. PhD in physics and an active record of independent research within a specialized subfield (e.g., High Energy/Mathematical Physics, Biophysics/Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation/Cosmology, Quantum Information, or Optical Materials).
  2. Experience as a postdoctoral researcher, research fellow, junior/assistant professor, or senior research scientist.
  3. Recent (last ~5 years) representative publications in the relevant subfield, with arXiv or DOI links.
  4. Advanced proficiency with LaTeX, SymPy, Python, and Jupyter for theoretical modeling and computational validation.
  5. Demonstrated skill in reviewing the work of others—through peer review, supervision, dissertation committees, or group seminars.
  6. Exceptional written communication skills with the ability to convey nuanced, constructive feedback with technical rigor.
  7. Reliable access to high-speed internet and a computer suitable for rigorous technical work.