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Temporary Data Annotation information

What is the difference between Temporary Data Annotation vs Data Labeler?

AspectTemporary Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailSimilar, often no formal certification required
Work EnvironmentRemote or on-site, project-basedRemote or on-site, often similar settings
Industry UsageUsed in AI/ML projects for training dataUsed in AI/ML, computer vision, NLP tasks
Search & Comparison IntentYesYes

Temporary Data Annotation involves short-term tasks focused on labeling data for AI models, often project-based. Data Labeler is a similar role, typically performing the same tasks but may be a more permanent or ongoing position. Both roles require basic skills and are used extensively in AI/ML industries, with overlapping work environments and employer types.

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Temporary Data Annotation jobs near you
Infographic showing various Temporary Data Annotation job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Scientist Contractor, Computational Biology

CAMP4 Therapeutics

Cambridge, MA

$64K - $64K/yr

Contractor

Re-posted 28 days ago

Job description

Position Title: Data Scientist Contractor, Computational Biology (6-month contract)
Reports To: Senior Director, Head of Data Sciences
Location: Cambridge, MA
Join the adventure!
CAMP4 is seeking a Data Science Contractor for a 6-month temporary contract assignment, specializing in Computational Biology, Bioinformatics, or Systems Biology, to support the processing, analysis, visualization, and interpretation of next-generation sequencing datasets. This assignment will have a particular focus on RNA-seq, scRNAseq, and long-read sequencing data, including Nanopore and PacBio platforms.
The successful candidate will apply state-of-the-art computational tools and, where needed, develop fit-for-purpose analytical approaches to interrogate complex genomics datasets. This role will help generate focused biological hypotheses to support target identification, target validation, and drug discovery programs. The candidate will work closely with experimental biologists and data scientists to systematically apply hypothesis-driven genomics approaches to advance CAMP4’s understanding of transcriptional mechanisms of disease and therapeutic strategies derived from them.

Key Responsibilities:
  • Process, analyze, visualize, and interpret next-generation sequencing (NGS) datasets, with an emphasis on bulk RNA-seq, scRNAseq, and long-read RNA sequencing, including Nanopore and PacBio sequencing data.
  • Execute bioinformatics analyses according to predefined analysis plans, including quality control, alignment, quantification, differential expression analysis, isoform/transcript analysis, splicing analysis, and integrative interpretation of results.
  • Collaborate closely with cross-functional teams, including experimental biologists, computational scientists, and project teams, to develop, refine, and execute research plans.
  • Provide clear biological interpretation and scientific context for computational results to support target discovery, validation, and mechanistic understanding.
  • Evaluate, implement, and apply new bioinformatics methods, tools, and emerging technologies relevant to transcriptomics, long-read sequencing, and functional genomics.
  • Develop scripts, workflows, and software tools where gaps exist to enable reproducible and scalable data analysis.
  • Provide conceptual input into analysis plans, including analytical strategy, study design, prioritization, and interpretation of key results.
  • Participate in cross-functional discussions to refine project goals, identify key priorities, and communicate findings effectively to both computational and experimental scientists.
  • Demonstrate strong ownership, attention to detail, and a sense of urgency in delivering high-quality analyses that support the discovery of breakthrough medicines for patients.
Qualifications:
Education amp; Experience
  • PhD in Bioinformatics, Computational Biology, Systems Biology, or a related field with 3+ years of relevant industry or postdoctoral experience.
Skills amp; Competencies
  • Strong hands-on experience analyzing NGS datasets, especially RNA-seq, scRNAseq, and long-read sequencing data from Nanopore and/or PacBio platforms.
  • Familiarity with long-read sequencing tools and workflows for transcript discovery, isoform characterization, or full-length transcript analysis is highly desirable.
  • Experience with additional functional genomics datasets, such as ATAC-seq, ChIP-seq, and PRO-seq.
  • Solid background in statistics and strong programming skills in Python and/or R.
  • Experience working in a Linux environment and using high-performance computing clusters and/or cloud computing platforms such as AWS.
  • Familiarity with human genome annotation resources, biological pathway databases, and systems biology concepts.
  • Strong commitment to reproducible research, best practices in software development, documentation, and version control.
  • Excellent collaboration and communication skills, with the ability to explain computational results clearly to experimental scientists and cross-functional teams.
  • Strong attention to detail, high professional integrity, and commitment to excellence in execution.
  • Creative and solution-oriented with the ability to develop fit-for-purpose approaches for diverse data and project needs.
  • Passionate about applying computational biology and genomics to translate fundamental scientific discoveries into medicines that improve patients’ lives.
Compensation:
Pay rate for this role will be determined based on the candidate’s skills and experience.

About CAMP4:
CAMP4 is developing disease-modifying treatments for a broad range of genetic diseases where amplifying healthy protein may offer therapeutic benefits. Our approach amplifies mRNA by harnessing a fundamental mechanism of how genes are controlled. To amplify mRNA, our therapeutic ASO drug candidates target regulatory RNAs (regRNAs), which act locally on transcription factors and are the master regulators of gene expression. CAMP4’s proprietary RAPTM Platform enables the mapping of regRNAs and design of optimal chemistry to generate potent therapeutic candidates to address hundreds of genetic diseases across multiple tissues. Learn more about us at www.camp4tx.com and follow us @CAMP4tx.

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