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Datasets Jobs (NOW HIRING)

IHRC INCORPORATED

Epidemiologist II

Atlanta, GA · On-site

Clean, merge, and maintain datasets from multiple sources to ensure consistency and usability. * Assist in aligning variables, standardizing naming conventions, and reconciling discrepancies across ...

SIG Susquehanna

$140 - $200/hr

Build point-in-time-correct datasets: preserving as-delivered history and handling vendor restatements, revisions, and backfills, so backtests see exactly what was knowable at the time * Design ...

Sciforium

Foundation Model Data Engineer

San Francisco, CA · On-site

$155K - $210K/yr

Own the end-to-end creation of pre-training datasets for LLMs. This includes defining the mix of web data, code, books, and technical papers to optimize for downstream model performance. * Petabyte ...

Columbia Technology Partners

$120 - $180/hr

Create feature vectors and datasets suitable for analytics development, testing, and model training. * Generate reports, visualizations, and presentations that communicate findings and ...

Hired Recruiters

Developer Evangelist

San Francisco, CA · On-site +1

As a Developer Evangelist, you will promote our main product TensorBay and our Open Datasets platform in the AI communities by sharing your knowledge and experience with datasets and their management ...

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How much do datasets jobs pay per year?

As of Sep 3, 2026, the average yearly pay for datasets in the United States is $142,829.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,500.00 and $175,000.00 per year, depending on experience, location, and employer.

What is the difference between Datasets vs Data Analysts?

AspectDatasetsData Analysts
Required credentialsNone specific; often familiarity with data formats and toolsBachelor's degree in data-related fields; skills in data analysis tools
Work environmentData repositories, databases, data warehousesOffice settings, data analysis software, reporting tools
Employer and industry usageUsed by data analysts, data scientists, and database managersUsed by business teams, data analysts, and decision-makers
Common search and comparison intentUnderstanding data sources and structuresInterpreting data, generating reports, making decisions

Datasets are collections of raw data used as sources for analysis, while Data Analysts interpret and analyze these datasets to generate insights and support decision-making. Datasets serve as the foundational data, whereas Data Analysts apply skills to extract value from them.

What cities are hiring for Datasets jobs?

Cities with the most Datasets job openings:

What states have the most Datasets jobs?

States with the most job openings for Datasets jobs include:

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Datasets jobs near you
Infographic showing various Datasets job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 94% Full Time, 2% Part Time, and 3% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $142,829 per year, or $68.7 per hour.

Epidemiologist II

IHRC INCORPORATED

Atlanta, GA • On-site

Full-time

Re-posted 19 days ago

Job description

Description

ANTICIPATED START DATE:  2 weeks after candidate identification

TRAVEL:  As required to fulfill the responsibilities of the position


IHRC Inc. seeks a dedicated and experienced Epidemiologist II to support our clients at Centers for Disease Control and Prevention (CDC)/Coronavirus and Other Respiratory Viruses Division (CORVD). CORVD's mission is to provide the health of people by preventing illness, disability and death from respiratory viruses through public health science and practice in the United States and globally. This position is needed for accomplishing CORVD's mission. Epidemiologist III will provide technical assistance to support regional capacity to conduct surveillance, detection, and response to events of public health significance. 

  • Support management and organization of respiratory hospitalization surveillance datasets (e.g., COVID-19, RSV). 
  • Clean, merge, and maintain datasets from multiple sources to ensure consistency and usability.
  • Assist in aligning variables, standardizing naming conventions, and reconciling discrepancies across datasets and time. 
  • Perform routine data validation checks to identify missing, inconsistent, or out-of-range values. 
  • Generate and maintain basic QA reports and track data issues and resolutions. 
  • Contribute to the development and upkeep of data dictionaries and metadata documentation. 
  • Assist in drafting and maintaining standard operating procedures (SOPs) for data workflows. 
  • Support data ingestion, transformation, and preparation for analysis and reporting. 
  • Create simple, user-friendly summaries or guides to support data users and stakeholders. 
  • Collaborate with epidemiologists and team members to ensure data quality and consistency. 
  • Maintain data security and confidentiality in accordance with project requirements.      
  • Work with structured and semi-structured datasets across platforms (e.g., Excel, SQL, REDCap, or cloud environments). 
  • Perform data cleaning, transformation, and basic harmonization tasks. 
  • Support merging of datasets and validation of outputs. 
  • Assist in tracking and documenting changes in data structure over time. 
  • Execute predefined QA checks and flag data quality issues. 
  • Maintain logs of data issues, corrections, and updates. 
  • Update data dictionaries and documentation as datasets evolve. 
  • Follow established data governance and documentation standards.

Requirements

  •     MS with 0-5+ years' experience or BA/BS with 5-10+ years' experience.

Desired Qualifications

  • Experience working with CDC staff at multiple organizational levels.
  • Proficiency in at least one: SQL, R, Python, or SAS. 
  • Experience working with large datasets (public health or healthcare data preferred). 
  • Familiarity with Excel and data cleaning techniques. 
  • Exposure to cloud platforms (e.g., Databricks) or willingness to learn. 
  • Basic understanding of data validation and QA processes. 
  • Communicate data issues and findings clearly to team members. 
  • Work collaboratively with technical and non-technical stakeholders. 
  • Follow established processes and escalate issues when needed. 
  • Exposure to public health or surveillance data systems. 
  • Experience with basic automation or scripting for data checks. 
  • Familiarity with metadata, data dictionaries, or documentation practices. 
  • Introductory experience with AI-assisted tools for data review or validation. 
  • Detail-oriented with strong organizational skills. 
  • Able to follow structured processes and maintain consistency. 
  • Comfortable working with moderately complex datasets. 
  • Proactive but able to work within defined guidance and frameworks. 
  • Strong written and verbal communication skills.

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