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Part Time Remote Pharmaceutical Validation Engineer Jobs in Minnesota

micro1 AI

Director of Biostatistics

Minneapolis, MN · Remote

$60 - $65/hr

Remote micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a ... Author and review evaluation tasks that require deriving, reproducing, or validating statistical ...

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Part Time Remote Pharmaceutical Validation Engineer information

What are the key skills and qualifications needed to thrive as a part time remote pharmaceutical validation engineer?

To thrive as a Part Time Remote Pharmaceutical Validation Engineer, you need expertise in pharmaceutical processes, quality assurance, and regulatory compliance, usually supported by a degree in engineering or a related field. Familiarity with validation tools, documentation systems, and regulatory standards such as FDA 21 CFR Part 11 and GAMP is typically required. Strong problem-solving abilities, attention to detail, and clear communication skills are essential for collaborating remotely and ensuring compliance. These skills and qualifications ensure the safe, efficient, and compliant operation of pharmaceutical manufacturing processes, even in a remote work environment.

What is a part time remote pharmaceutical validation engineer?

A Part Time Remote Pharmaceutical Validation Engineer is a professional who works part-time hours, often from a remote location, to ensure that pharmaceutical processes, equipment, and systems meet regulatory and quality standards. Their responsibilities include developing validation protocols, conducting risk assessments, reviewing documentation, and ensuring compliance with Good Manufacturing Practices (GMP). This role is essential for maintaining product safety and efficacy in the pharmaceutical industry and often involves collaboration with cross-functional teams and regulatory bodies.

What are some common challenges of working as a part-time remote pharmaceutical validation engineer, and how can they be managed?

One common challenge in this role is maintaining clear communication with on-site teams and ensuring alignment on project timelines and regulatory requirements, since much of the validation work may require coordination with laboratory staff and quality assurance personnel. Remote engineers must also adapt to varying documentation standards and digital validation tools used by different clients. Staying proactive by scheduling regular video meetings, utilizing project management platforms, and keeping meticulous records can help manage these challenges. Additionally, keeping up-to-date with evolving industry regulations and validation best practices is essential for delivering effective results remotely.
What are popular job titles related to Part Time Remote Pharmaceutical Validation Engineer jobs in Minnesota? For Part Time Remote Pharmaceutical Validation Engineer jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Part Time Remote Pharmaceutical Validation Engineer jobs in Minnesota look for? The top searched job categories for Part Time Remote Pharmaceutical Validation Engineer jobs in Minnesota are:
Part Time Remote Pharmaceutical Validation Engineer jobs near you
Infographic showing various Part Time Remote Pharmaceutical Validation Engineer job openings in Minnesota as of June 2026, with employment types broken down into 100% Part Time. Highlights an 100% Remote job distribution.

Director of Biostatistics

micro1 AI

Minneapolis, MN • Remote

$60 - $65/hr

Part-time

Posted 6 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 — 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.

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