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Part Time Data Analyst R Programming Jobs in Houston, TX

... data strategies under ICH E9(R1). * Proficiency in SAS and/or R, with the ability to independently reproduce analyses from written specifications. * Ability to interpret SAPs and ensure reported ...

Prompt Engineering * AI Output Evaluation * Financial Analysis * Technical & Report Writing ... Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ...

... analysis. * Evaluate and synthesize findings from biological, chemical, and clinical data sources ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

... analysis. * Evaluate and synthesize findings from biological, chemical, and clinical data sources ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

... analysis. * Evaluate and synthesize findings from biological, chemical, and clinical data sources ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

Showing results 41-60

Part Time Data Analyst R Programming information

See Houston, TX salary details

$32.5K

$78.9K

$129.9K

How much do part time data analyst r programming jobs pay per year?

As of Aug 18, 2026, the average yearly pay for part time data analyst r programming in Houston, TX is $78,919.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,700.00 and $92,600.00 per year, depending on experience, location, and employer.

What is the difference between Part Time Data Analyst R Programming vs Part Time Data Analyst Python?

AspectPart Time Data Analyst R ProgrammingPart Time Data Analyst Python
Required SkillsProficiency in R, data visualization, statistical analysisProficiency in Python, data manipulation, machine learning
Work EnvironmentData analysis, reporting, statistical modelingData analysis, automation, machine learning projects
Industry UsageResearch, healthcare, financeTech, finance, marketing

Both roles involve data analysis in a part-time setting but differ mainly in programming language expertise. R is favored for statistical analysis and visualization, while Python is preferred for automation and machine learning tasks. Your choice depends on the specific tools and industry focus.

What are the most commonly searched types of Data Analyst R Programming jobs in Houston, TX?

The most popular types of Data Analyst R Programming jobs in Houston, TX are:

What are popular job titles related to Part Time Data Analyst R Programming jobs in Houston, TX?

For Part Time Data Analyst R Programming jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Part Time Data Analyst R Programming jobs in Houston, TX look for?

The top searched job categories for Part Time Data Analyst R Programming jobs in Houston, TX are:

What cities near Houston, TX are hiring for Part Time Data Analyst R Programming jobs?

Cities near Houston, TX with the most Part Time Data Analyst R Programming job openings:

Infographic showing various Part Time Data Analyst R Programming job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $78,919 per year, or $37.9 per hour.

Director of Biostatistics

micro1 AI

Houston, TX • 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 — 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.