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Remote R Programming Jobs in New Jersey (NOW HIRING)

Remote micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a ... Proficiency in SAS and/or R, with the ability to independently reproduce analyses from written ...

... programming language, such as R or SAS, is required. * 3+ years of experience of relevant ... Remote or field-based positions will have different workplace arrangements which will be indicated ...

Data Engineer

Parsippany, NJ · Remote

$105K - $151K/yr

Strong proficiency in SQL and at least one programming language (Python, Scala, Java). * Experience ... Position is Parsippany, NJ preferred; remote considered The US base salary range for this full-time ...

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Remote R Programming information

What does a remote R programmer do?

Remote R Programmers often work on projects involving data cleaning, statistical modeling, and creating data visualizations for business or scientific insights. They may be responsible for developing automated data workflows, building predictive models, or generating reproducible reports using R Markdown or Shiny dashboards. Additionally, remote work usually requires frequent collaboration with data scientists, analysts, or cross-functional teams via virtual meetings and project management platforms. This role allows you to contribute to diverse industries, ranging from healthcare to finance, and offers opportunities to continuously expand your technical expertise.

What is a remote R programming?

A Remote R Programming job involves using the R programming language for data analysis, statistical modeling, and visualization while working from a remote location. Professionals in this role may work in fields such as data science, finance, healthcare, or research. Tasks often include data cleaning, building predictive models, and generating reports using R packages like ggplot2, dplyr, and tidymodels. Remote R programmers typically collaborate with teams through online communication tools and version control systems like Git. This role requires strong analytical skills and the ability to work independently while delivering data-driven insights.

What are the key skills and qualifications needed to thrive in the remote R programming position?

To thrive as a Remote R Programmer, you need strong proficiency in R programming, data analysis, and statistics, typically supported by a degree in a quantitative field such as computer science, statistics, or data science. Familiarity with version control systems like Git, data visualization libraries (e.g., ggplot2), and experience with cloud-based collaboration tools is highly valued. Excellent communication skills, self-motivation, and the ability to work independently are important soft skills for remote success. These competencies ensure that you can efficiently deliver high-quality analytical solutions and collaborate with distributed teams.

What are the most commonly searched types of R Programming jobs in New Jersey? The most popular types of R Programming jobs in New Jersey are:
What job categories do people searching Remote R Programming jobs in New Jersey look for? The top searched job categories for Remote R Programming jobs in New Jersey are:
What cities in New Jersey are hiring for Remote R Programming jobs? Cities in New Jersey with the most Remote R Programming job openings:
Infographic showing various Remote R Programming job openings in New Jersey as of August 2026, with employment types broken down into 87% Full Time, 6% Part Time, and 7% Contract. Highlights an 100% Remote job distribution.

Director of Biostatistics

micro1 AI

Paterson, NJ • Remote

$60 - $65/hr

Part-time

Posted 7 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.