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Data Assistant Jobs (NOW HIRING)

campus4tech

Data Engineer

Manhattan, NY · On-site

$126.20K - $151.60K/yr

Leverage GenAI/Data Assist tools to accelerate data science workflows. * Collaborate with stakeholders to align models with business outcomes. * Build and refine machine learning models under ...

Dhalite Inc.

Data Operations Associate

Columbus, OH

Identify trends, patterns, and insights from data * Assist in maintaining accurate databases and records * Support teams by providing data-related information * Create charts, summaries, and ...

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millenniumsoft

Clinical Data Entry

Franklin Lakes, NJ · On-site

Clinical Data Entry Assistant Location : Franklin Lakes, NJ Duration : 12+ Month(s) Contract Start Time : 8:00 AM End Time : 5:00 PM Total Hours/week : 40.00 Qualifications • Minimum HS diploma • ...

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How much do data assistant jobs pay per hour?

As of May 30, 2026, the average hourly pay for data assistant in the United States is $19.78, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $20.19 per hour, depending on experience, location, and employer.

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

To excel as a Data Assistant, you need strong attention to detail, proficiency in data entry, and a basic understanding of data management principles, often supported by a high school diploma or equivalent. Familiarity with spreadsheet software such as Microsoft Excel, database platforms, and data visualization tools is typically required. Excellent organizational skills, reliability, and effective communication set top performers apart in this role. These abilities are vital for ensuring data accuracy, supporting efficient workflows, and facilitating informed decision-making within organizations.

What are some common challenges Data Assistants face when managing large datasets, and how can they overcome them?

Data Assistants often encounter challenges such as data inconsistencies, missing information, and time-consuming data entry tasks when handling large datasets. To overcome these issues, it’s important to develop strong attention to detail, utilize data validation tools, and follow established data management protocols. Collaborating closely with data analysts and IT teams can also help identify and resolve data quality problems more efficiently, ensuring that the information remains accurate and reliable for stakeholders.

What are Data Assistants?

Data Assistants are professionals who support data management processes within an organization. Their responsibilities typically include collecting, entering, cleaning, and maintaining data to ensure its accuracy and accessibility. They often work with spreadsheets, databases, and specialized software to organize and analyze information, making it easier for teams to make data-driven decisions. Data Assistants may also help prepare reports and collaborate with other departments to support research or business operations.

What is the difference between Data Assistant vs Data Analyst?

AspectData AssistantData Analyst
Required CredentialsHigh school diploma or equivalent; some roles may require basic certificationsBachelor's degree in data-related fields; certifications like Microsoft Excel or SQL are common
Work EnvironmentOffice settings, data entry centers, or remoteOffice environments, research firms, or corporate settings
Employer & Industry UsageAdministrative support in various industries, including healthcare, education, and retailData-driven decision making in finance, marketing, healthcare, and tech

While Data Assistants focus on data entry, organization, and basic support tasks, Data Analysts interpret data to provide insights and strategic recommendations. Both roles are essential but differ in complexity and scope.

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Data Assistant jobs near you

Data Engineer

campus4tech

Manhattan, NY • On-site

$126.20K - $151.60K/yr

Full-time

Posted 4 days ago

Job description

Job Title- Data Engineer
Location- New York, NY 10112
Reporting Type- Onsite
Duration: 10 months
Summary
This role involves building and delivering advanced data science and AI/ML solutions in an agile environment, with a focus on rapid iteration and business impact. The Data Engineer will drive end-to-end model development, including propensity modeling and integration with data engineering pipelines, while leveraging GenAI to accelerate outcomes. Supporting roles include Data Engineers who will collaborate to build models, manage data pipelines, and ensure scalable data infrastructure. Experience in the HR domain is a plus.
Responsibilities
  • Lead end-to-end data science projects using agile and iterative approaches.
  • Develop and deploy AI/ML models, including propensity modeling.
  • Drive data engineering requirements to support model development and optimization.
  • Leverage GenAI/Data Assist tools to accelerate data science workflows.
  • Collaborate with stakeholders to align models with business outcomes.
  • Build and refine machine learning models under guidance.
  • Perform data analysis, feature engineering, and model validation.
  • Support deployment and testing of AI/ML solutions.

Requirements
Data engineer (C level) - should have experience building pipelines in AWS and cloud databases. Structured and unstructured data sets. Loading of data into S3 as well as tabular schemas. Databricks experience preferred.

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