ZipRecruiter

Log In

1

Overnight Ai Data Labeling Jobs in Ohio (NOW HIRING)

RELX

AI Data Analyst

Dayton, OH · On-site

Support basic semantic labeling or categorization efforts that improve AI retrieval and reasoning ... Help ensure data included in AI retrieval scenarios is appropriate, governed, and up to date.

NEURA Robotics

$70 - $90/hr

Your mission & challenges As an AI Data Annotation Specialist, you will operate at the intersection ... Apply pre-labeling techniques using existing models to accelerate annotation processes * Validate ...

HumanSignal

Delivery Lead

Columbus, OH · On-site

$90K - $130K/yr

Drive delivery across custom data pipelines and expert labeling workflows, translating researcher requirements into clear operational plans * Collaborate with AI lab researchers and procurement ...

HumanSignal

Delivery Lead

Columbus, OH · On-site

$90K - $130K/yr

Drive delivery across custom data pipelines and expert labeling workflows, translating researcher requirements into clear operational plans * Collaborate with AI lab researchers and procurement ...

HumanSignal

High Volume (TOFU) Recruiter

Columbus, OH · On-site +1

$55K - $100K/yr

About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data ... When a pipeline dries up or a new program spins up overnight, you don't wait to be told -- you move.

next page

Showing results 1-20

All JobsAi Data Labeling JobsOvernight Ai Data Labeling JobsOvernight Ai Data Labeling Jobs in Ohio

Overnight Ai Data Labeling information

What is overnight AI data labeling?

Overnight AI data labeling involves annotating and categorizing data, such as images, videos, or text, during nighttime hours to prepare it for use in training artificial intelligence models. This work typically requires attention to detail and accuracy, as the quality of labeled data directly affects AI performance. Overnight shifts are often used by companies to ensure a continuous workflow and to accelerate project timelines. Data labelers may use specialized tools to tag, classify, or segment data according to specific guidelines provided by clients or employers.

What are the key skills and qualifications needed to thrive as an overnight AI data labeler, and why are they important?

To thrive as an Overnight AI Data Labeler, you need strong attention to detail, accuracy, and the ability to follow complex instructions, often supported by a high school diploma or relevant experience. Familiarity with data labeling platforms, annotation tools, and basic computer applications is typically required. Strong time management, self-motivation, and dependable communication are essential soft skills for working independently during overnight shifts. These skills ensure high-quality, consistent data annotation that directly impacts the performance and reliability of AI models.

What are some common challenges faced by overnight AI data labeling professionals, and how can they be addressed?

Overnight AI data labeling professionals often face challenges such as maintaining focus during late hours, managing screen fatigue, and adapting to fast-paced project requirements. To address these, it's important to establish a consistent sleep schedule, take regular short breaks to rest your eyes, and stay organized by tracking progress against nightly goals. Collaborating with teammates through scheduled check-ins or chat platforms can also help maintain motivation and ensure high-quality results, even during less traditional work hours.

What is the difference between Overnight Ai Data Labeling vs Data Annotation Specialist?

AspectOvernight Ai Data LabelingData Annotation Specialist
CredentialsBasic computer skills, attention to detailSimilar, often requires familiarity with annotation tools
Work EnvironmentRemote or flexible hours, often project-basedOffice or remote, depending on employer
Industry UsageCommon in AI and machine learning projectsUsed across AI, healthcare, autonomous vehicles
Search IntentFocus on overnight or flexible schedulingBroader annotation roles, less emphasis on timing

Overnight Ai Data Labeling typically involves quick turnaround tasks with flexible hours, often performed remotely. Data Annotation Specialists may have similar skills but usually work regular hours and may handle more complex annotation tasks. Both roles are essential in AI development, but Overnight Ai Data Labeling emphasizes speed and flexibility, whereas Data Annotation Specialists focus on detailed, accurate labeling across various industries.

What are the most commonly searched types of Ai Data Labeling jobs in Ohio?

The most popular types of Ai Data Labeling jobs in Ohio are:

What are popular job titles related to Overnight Ai Data Labeling jobs in Ohio?

For Overnight Ai Data Labeling jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Overnight Ai Data Labeling jobs in Ohio look for?

The top searched job categories for Overnight Ai Data Labeling jobs in Ohio are:

What cities in Ohio are hiring for Overnight Ai Data Labeling jobs?

Cities in Ohio with the most Overnight Ai Data Labeling job openings:

Overnight Ai Data Labeling jobs near you
Infographic showing various Overnight Ai Data Labeling job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AI Data Analyst

RELX

Dayton, OH • On-site

Full-time

Medical, Life

Re-posted 29 days ago

Job description

Are you passionate about improving data quality and readiness to unlock the full potential of AI solutions?

Do you enjoy collaborating across teams to ensure data is structured, governed, and usable for intelligent systems?

About the Business:

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below,

https://risk.lexisnexis.com

About the Team:

We are a newly formed Enterprise AI team focused on enabling agent-based solutions across the organization. We build and manage the environments, platforms, and guardrails that allow teams to create, test, and scale AI agents safely and efficiently turning experimentation into real business impact.

We're a team of curious builders and operators who are constantly exploring, learning, and applying new AI tools and approaches to solve real-world problems and improve how work gets done.

About the Role:

We are seeking an AI Data Analyst to support teams in preparing and maintaining AIready data for use in AI tools, copilots, and intelligent agents. This role focuses on data readiness, quality, metadata, and governance, helping teams understand how to structure, document, and manage their data so it can be safely and effectively used by AI systems.

The AI Data Analyst partners with data engineering, AI, and governance teams to assess data readiness, identify gaps and recommend improvements. This role does not own endtoend data pipelines and is not expected to be a deep technical expert in RAG or embeddings, but should have a solid working understanding of AIdriven data needs.

Responsibilities:

AI Data Readiness Support

  • Work with product and delivery teams to assess whether datasets and content are fit for AI use cases.
  • Help teams understand and apply AI data readiness standards, including quality, freshness, metadata, and access expectations.
  • Identify common data issues that impact AI outcomes (e.g., stale data, unclear ownership, missing metadata) and recommend remediation steps.
  • Contribute to repeatable checklists, guidance, or documentation that help teams prepare data for AI.

Data Quality & Relevance

  • Support data quality checks focused on accuracy, completeness, consistency, and timeliness for AIconsumed data.
  • Assist in monitoring and validating data freshness and relevance, escalating issues to engineering or data owners as needed.
  • Help teams improve data clarity and usability to reduce ambiguity in AI outputs.

Metadata & Semantic Enablement

  • Assist teams in improving metadata, documentation, and business descriptions so AI systems can better interpret content.
  • Support basic semantic labeling or categorization efforts that improve AI retrieval and reasoning (in coordination with engineering teams).
  • Promote good content hygiene practices (clear structure, consistent naming, wellscoped documents).

AI Data Sources & Retrieval (Support Role)

  • Support the upkeep and documentation of approved data sources used by AI solutions.
  • Help ensure data included in AI retrieval scenarios is appropriate, governed, and up to date.
  • Collaborate with AI and platform teams on data inclusion/exclusion decisions without owning technical implementation.

Governance, Lineage & Compliance Awareness

  • Help teams align AIconsumed data with enterprise governance requirements, including classification, access controls, and retention.
  • Support basic data lineage and ownership documentation for AIrelevant datasets.
  • Partner with governance and security teams by surfacing risks or gaps; does not act as final approval authority.

What This Role Does Not Own

  • Does not design or own endtoend production data pipelines.
  • Does not act as the primary technical owner for RAG frameworks, vector databases, or embedding strategies.
  • Does not make final governance or compliance decisions independently.

Requirements:

  • Proven experience in data analysis, analytics engineering, data operations, or data quality roles.
  • Good understanding of data quality principles and how poor data impacts downstream systems.
  • Experience working with structured and unstructured data (tables, files, documents, knowledge assets).
  • Proficiency in SQL and comfort investigating data issues.
  • Familiarity with data governance fundamentals (classification, access controls, ownership, retention).
  • Strong communication skills and ability to explain data concepts to nontechnical stakeholders.

Preferred Qualifications

  • Exposure to AIenabled products, copilots, or searchbased solutions.
  • Basic familiarity with AI data concepts such as semantic search, embeddings, or retrieval patterns.
  • Experience working in enterprise or regulated environments.
  • Experience contributing to standards, playbooks, or shared data practices.

What Success Looks Like

  • Teams can reliably prepare datasets that meet AI readiness expectations with less rework.
  • AI solutions benefit from more relevant, uptodate, and understandable data.
  • Clear ownership and documentation exist for data used by AI systems.
  • Strong collaboration between delivery teams, data engineering, and governance.

Working for You:

We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

  • Medical Inpatient and Outpatient Insurance: Coverage for your healthcare needs.
  • Life Assurance Policies: Providing financial security for your loved ones.
  • Modern Family Benefits: Support for maternity, paternity, and adoption needs.
  • Long Service Award: Recognition for your dedication and loyalty.
  • Celebratory Allowance/Gifts: Marking special occasions to celebrate with you.
  • Flexible Benefits Plan : Offering you wider choice of services and products
  • Employee Assistance Program : Access support for personal and work-related challenges.
  • Flexible Working Arrangements: Balance work and personal life effectively.
  • Access to Learning and Development Resources: Empowering your professional growth.

Risk benefit statement
Learn more about the LexisNexis Risk team and how we work: https://relx.wd3.myworkdayjobs.com/RiskSolutions/page/21c296c982531000b79663f3194b0000

U.S. National Base Pay Range: $78,800 - $131,300. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Ohio, the base pay range is $74,900 - $124,700. This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Formor please contact 1-855-833-5120.

Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here.

Please read our Candidate Privacy Policy.

We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

USA Job Seekers:

EEO Know Your Rights.

Apply