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Tidyverse Jobs (NOW HIRING)

ERC, Inc.

Data Scientist

Redstone Arsenal, AL · On-site

Deep knowledge of common programming languages (Python, R, Julia), data science packages and frameworks (Pandas, NumPy, Scikit-learn, tidyr, tidyverse). * Background working with common data ...

Prodege, LLC

Senior Data Scientist

El Segundo, CA · On-site

... tidyverse, or similar) and robust experience with common ML packages (scikit-learn or similar). • Ability to develop effective data visualizations that clearly communicate insights to business ...

ERC Inc.

Data Scientist

Huntsville, AL · On-site

Deep knowledge of common programming languages (Python, R, Julia), data science packages and frameworks (Pandas, NumPy, Scikit-learn, tidyr, tidyverse). Background working with common data ...

IQVIA, Inc.

Principal R Programmer

Durham, NC · On-site

$98K - $273K/yr

Must have advanced R programming skills, including tidyverse, ggplot2, Markdown, Quarto, Shiny, etc. Python and/or SAS programming skills are a plus, but not required. * Knowledge of CDISC standards ...

IQVIA

Principal R Programmer

Durham, NC · On-site

$98K - $273K/yr

Must have advanced R programming skills, including tidyverse, ggplot2, Markdown, Quarto, Shiny, etc. Python and/or SAS programming skills are a plus, but not required. * Knowledge of CDISC standards ...

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Tidyverse information

What are Tidyverse packages?

The Tidyverse is a collection of R packages designed for data science. These packages share an underlying design philosophy, grammar, and data structures, making it easy to manipulate, explore, and visualize data. The core Tidyverse packages include ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, and forcats, among others. They help streamline common data analysis tasks and are widely used by R programmers for efficient and readable code.

What are the key skills and qualifications needed to thrive as a Tidyverse Data Analyst, and why are they important?

To thrive as a Tidyverse Data Analyst, you need strong data manipulation, visualization, and statistical analysis skills, typically supported by a degree in statistics, data science, or a related field. Proficiency in R programming and mastery of Tidyverse packages (such as dplyr, ggplot2, tidyr, and readr) are essential, along with knowledge of version control systems like Git. Analytical thinking, attention to detail, and clear communication are standout soft skills in this role. These skills ensure accurate data insights, reproducible workflows, and effective collaboration with stakeholders for data-driven decision-making.

How does working as a Tidyverse data analyst typically involve collaboration with other teams or departments?

As a Tidyverse data analyst, collaboration is a core aspect of the role. You'll often work closely with stakeholders from various departments, such as marketing, finance, or product teams, to understand their data needs and translate them into actionable insights using R and the Tidyverse package suite. Regular communication is essential for gathering requirements, presenting findings, and ensuring that analyses align with business goals. Additionally, you may partner with data engineers or IT to access and manage datasets, and with other analysts to share best practices and streamline workflows.

What is the difference between Tidyverse vs Data Analyst?

AspectTidyverseData Analyst
Primary FocusData manipulation, visualization, and analysis using R packagesInterpreting data, creating reports, and supporting decision-making
Skills & ToolsR programming, ggplot2, dplyr, tidyr, readrExcel, SQL, statistical analysis, data visualization tools
Work EnvironmentData science teams, research labs, analytics departmentsBusiness, finance, marketing, healthcare sectors
Required CredentialsKnowledge of R, data analysis, statisticsDegree in statistics, data science, or related fields

While Tidyverse refers to a collection of R packages for data manipulation and visualization, Data Analysts utilize these tools along with other skills to interpret data and generate insights. Tidyverse is a technical toolkit, whereas Data Analyst is a role that applies these tools in various industries to support decision-making.

More about Tidyverse jobs
What cities are hiring for Tidyverse jobs? Cities with the most Tidyverse job openings:
What states have the most Tidyverse jobs? States with the most job openings for Tidyverse jobs include:
What job categories do people searching Tidyverse jobs look for? The top searched job categories for Tidyverse jobs are:
Tidyverse jobs near you
Infographic showing various Tidyverse job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, and 5% Part Time. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution.

Scientist/Sr. Scientist, Bioinformatics Data

Legend Biotech US

Somerset, NJ • Hybrid

Other

Posted 23 days ago

Job description

Legend Biotech is seeking a Scientist/Sr. Scientist, Bioinformatics Data as part of the Early Drug Development team based in Somerset, NJ.

Role Overview

We are seeking a highly motivated, passionate, and driven Bioinformatics Data Scientist with high scientific curiosity to join our research and development team. In this role, you will bridge the gap between complex biological datasets and actionable therapeutic insights. You will design, develop, and execute scalable computational pipelines to analyze high-dimensional genomic data.The ideal candidate possesses a deep curiosity for biological systems, an analytical mindset, and the technical skillset to tackle unstructured, diverse and complex multiomics challenges. Whether you come from a deep biological background with strong computational skills or a data science background with a proven track record in working with biological data, you will play a critical role in accelerating both our discovery and clinical pipeline.

Key Responsibilities

  • Data Analysis:
    • Analyze diverse and large-scale genomic datasets (e.g., RNA-seq, scRNA-seq, WES/WGS, epigenetic, or multi-omics data) to identify biomarkers, therapeutic targets, or disease mechanisms.
    • Apply advanced statistical, machine learning, and data-mining techniques to extract meaningful patterns from noisy biological data.
    • Perform quality control, normalization, and batch-correction across heterogeneous datasets.
  • Pipeline Development & Automation: 
    • Design, optimize, and maintain robust, scalable bioinformatics pipelines.
    • Implement version-controlled code architectures to ensure reproducibility and scalability of data analyses.
    • Procure and integrate existing biological databases with internal datasets.
  • Cross-Functional Collaboration:
    • Translate complex computational and statistical findings into clear biological narratives for experimental biologists, clinicians, and stakeholders.
    • Collaborate with IT and other functional groups.

Requirements

  •  Ph.D. or M.S. in Bioinformatics, Computational Biology, Data Science, Genomics, Biology, or a highly quantitative field.
  • Proven experience handling genomic data (Next-Generation Sequencing/NGS data analysis is required).
  • Ability to turn raw biological data into structured insights.
  •  Strong experience with AI application in data science.
  • Advanced proficiency in R (e.g., Bioconductor, Tidyverse) and/or Python (e.g., Pandas, NumPy, Scikit-learn).
  • Experience with standard bioinformatics tools (e.g., alignment tools, variant callers, single-cell toolkits like Seurat/Scanpy).
  • Experience with cloud computing platforms (AWS, GCP) and containerization (Docker, Singularity) is a strong plus.
  • A self-starting attitude with an intrinsic desire to stay ahead of the curve in emerging computational methods and biological technologies.
  • Proven ability to thrive in a fast-paced environment, manage multiple projects simultaneously, and pivot quickly based on data-driven feedback.
  • Exceptional critical thinking skills with a knack for debugging complex code and parsing unstructured data formats.
  • Creative, innovative and excellent communication and presentation skills.
  • This role is designed as the starting point of group effort to solve complex biological and clinical problems in a fast paced environment. We look for individuals who take extreme ownership of their expertise and training, and driven by the prospect of turning data into information, and information into knowledge.

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