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Contract Data Annotation Analyst Jobs in Phoenix, AZ

IDEALFORCE LLC

Data Analyst/SR (29689)

Phoenix, AZ · On-site

Company Description IDEALFORCE has a CONTRACT position available immediately for a DATA Analyst to join our customer in Phoenix Arizona. This is an ONSITE position. Please find below additional ...

Raytheon

Principal Analyst Data Manager

Phoenix, AZ · On-site

We are hiring a Principal Analyst Data Manager to work onsite in Tucson, Arizona. What You Will Do ... Identifies all data deliverables made part of a contract * Builds a data track in a Product Data ...

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All JobsContract Data Annotation Analyst JobsContract Data Annotation Analyst Jobs in Phoenix, AZ

Contract Data Annotation Analyst information

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$33.8K

$82.1K

$135K

How much do contract data annotation analyst jobs pay per year?

As of Sep 7, 2026, the average yearly pay for contract data annotation analyst in Phoenix, AZ is $82,054.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,100.00 and $96,300.00 per year, depending on experience, location, and employer.

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Data Scientist, Department of Internal Medicine (Phoenix)

University of Arizona

Phoenix, AZ

Full-time

Posted 4 days ago

University Of Arizona rating

7.4

Company rating: 7.4 out of 10

Based on 69 frontline employees who took The Breakroom Quiz

339th of 631 rated colleges and universities

Job description

  • Develop, maintain, and optimize computational pipelines for analysis of single-cell RNA sequencing, single-nucleus RNA sequencing, and spatial transcriptomics datasets.
  • Process and analyze large-scale genomic datasets generated from 10x Genomics Chromium, Visium, Visium HD, Xenium, and related platforms.
  • Perform quality control, clustering, cell type annotation, differential gene expression analysis, trajectory analysis, data integration, and multimodal analyses.
  • Apply machine learning, statistical, and bioinformatics approaches to identify biologically meaningful patterns and generate testable hypotheses.
  • Develop reproducible analysis workflows using Linux-based computing environments, high-performance computing resources, and version-controlled code repositories.
  • Generate publication-quality figures, visualizations, summaries, and reports for manuscripts, grant applications, presentations, and progress reports.
  • Work directly with faculty investigators to interpret results, troubleshoot analyses, and develop data-driven research strategies.
  • Assist with management, organization, storage, and archival of large genomic datasets.
  • Collaborate with laboratory personnel regarding experimental design, sample preparation, sequencing strategies, and downstream analyses.
  • Coordinate data transfer, sequencing submissions, sample tracking, and communication with sequencing and genomics service providers.
  • Contribute to preparation of manuscripts, abstracts, presentations, and extramural grant applications.
  • Train students, staff, and investigators in computational analysis methods and best practices for genomic data analysis.
  • Participate in laboratory meetings, research seminars, and collaborative project discussions.
  • May assist with tissue collection, sample preparation, library construction, spatial transcriptomics workflows, and related laboratory activities as needed.

Knowledge, Skills, and Abilities:

  • Strong computational and analytical skills with demonstrated experience in biological, genomic, transcriptomic, or other large-scale scientific data analysis.
  • Proficiency in Linux/Unix operating systems and command-line environments.
  • Experience with Bash scripting and workflow automation.
  • Proficiency in R and/or Python programming for scientific computing and data visualization.
  • Experience with commonly used single-cell and spatial transcriptomics software packages.
  • Knowledge of machine learning, statistical analysis, dimensionality reduction, clustering methods, data visualization techniques and biological data integration approaches.
  • Ability to communicate complex computational findings to investigators with diverse scientific backgrounds, and work effectively in a collaborative multidisciplinary research environment.
  • Ability to manage multiple collaborative projects simultaneously while meeting deadlines.
  • Strong organizational skills, attention to detail, excellent written and verbal communication skills.

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