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Phd Statistics Jobs in Rhode Island (NOW HIRING)

Director of Biostatistics

Providence, RI ยท 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

Providence, RI ยท 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 ...

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Showing results 1-20

Phd Statistics information

See Rhode Island salary details

$23.5K

$92.8K

$171.8K

How much do phd statistics jobs pay per year?

As of Aug 18, 2026, the average yearly pay for phd statistics in Rhode Island is $92,787.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,451.00 and $121,386.00 per year, depending on experience, location, and employer.

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 Rhode Island?

The most popular types of Phd Statistics jobs in Rhode Island are:

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

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

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

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

What cities in Rhode Island are hiring for Phd Statistics jobs?

Cities in Rhode Island with the most Phd Statistics job openings:

Infographic showing various Phd Statistics job openings in Rhode Island as of August 2026, with employment types broken down into 79% Full Time, 19% Part Time, and 2% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $92,787 per year, or $44.6 per hour.

Director of Biostatistics

micro1 AI

Providence, RI โ€ข Remote

$60 - $65/hr

Part-time

Posted 14 days ago


Job description

Role Title: Biostatistician


Role Type: Contractor


Location: Remote


micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a dynamic customer project focused on AI-assisted clinical research. 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 โ€” your domain knowledge is what matters.


Scope of Work

  1. Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs).
  2. Apply expert judgment to assess the correctness and consistency of reported estimates, confidence intervals, p-values, analysis populations, and missing data handling in alignment with the statistical analysis plan (SAP).
  3. Identify discrepancies between statistical outputs and their narrative descriptions in clinical study reports (CSR), including subtle errors in population definitions, censoring rules, or multiplicity handling.
  4. Establish defensible ground truth for each evaluation task, documenting the derivation process to enable independent verification.
  5. Provide structured written rationales distinguishing true statistical errors from acceptable methodological alternatives, employing clear and concise communication.
  6. Collaborate with a multidisciplinary project team, providing statistical insights and feedback as needed to refine evaluation tasks and criteria.


Preferred Qualifications

  1. 5+ years as a biostatistician supporting clinical trials at a sponsor, CRO, or academic trials unit.
  2. Hands-on experience producing or quality controlling TFLs for regulatory submissions and working directly from CDISC SDTM/ADaM datasets.
  3. Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies under ICH E9(R1).
  4. Proficiency in SAS and/or R, with the ability to independently reproduce analyses from written specifications.
  5. Ability to interpret SAPs and ensure reported results are consistent with pre-specified analyses.
  6. Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field.
  7. Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or reviewing CSR statistical sections, oncology endpoint expertise, and exposure to AI-assisted statistical review tools.