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Remote Data Labeling Analyst Jobs in Kentucky (NOW HIRING)

Toloka

As part of this role, you will not only design and implement data labeling pipelines but also act ... Analyze data to identify failure modes, inefficiencies, and opportunities for improvement.

NV5

Senior Analyst

Lexington, KY · On-site +1

$77K - $102K/yr

... remote sensing, data management, quality control, and project delivery teams. Work Environment ... Conduct complex geospatial analyses using transportation-related data sources, including roadway ...

Cayenta

(Remote) Support Analyst

Canada, KY · Remote

Troubleshoot application, data, architecture, and interface-related problems * Communicate ... Strong analytical skills with the ability to make sound, independent decisions * Self-motivated ...

The Phia Group

Data Engineer (Remote)

Louisville, KY · On-site +1

$104K - $125K/yr

Collaborate with analysts, stakeholders, and product owners to translate business needs into data requirements and stable technical implementations * Enable data for AI/ML use cases by preparing ...

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Remote Data Labeling Analyst information

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

To thrive as a Remote Data Labeling Analyst, you need strong attention to detail, analytical thinking, and basic data management skills, typically supported by a high school diploma or higher. Familiarity with annotation tools, data labeling platforms, and sometimes basic programming or spreadsheet software is required. Strong communication, time management, and the ability to work independently are crucial soft skills for excelling remotely. These abilities ensure high-quality, accurate data labeling that directly impacts the effectiveness of AI and machine learning systems.

What are some common challenges faced by Remote Data Labeling Analysts, and how can they be addressed?

Remote Data Labeling Analysts often encounter challenges such as maintaining focus during repetitive tasks, managing time effectively across multiple projects, and ensuring high accuracy in labeling complex data sets. To address these challenges, it is helpful to follow structured workflows, take regular breaks to reduce fatigue, and leverage collaboration tools to communicate with team members for clarification or feedback. Staying updated with labeling guidelines and participating in regular training sessions can also help improve both productivity and quality of work.

What does a Remote Data Labeling Analyst do?

A Remote Data Labeling Analyst is responsible for reviewing, tagging, and annotating data—such as images, videos, text, or audio—to help train machine learning models. Working remotely, they use specialized software to classify or categorize this data according to specific guidelines. Their work is crucial for improving the accuracy and performance of artificial intelligence systems, as well-labeled data enables the AI to learn and make better predictions. This role typically requires attention to detail, consistency, and the ability to follow complex instructions.

What is the difference between Remote Data Labeling Analyst vs Remote Data Annotator?

AspectRemote Data Labeling AnalystRemote Data Annotator
CredentialsBasic data labeling skills, familiarity with annotation toolsSimilar credentials, often entry-level
Work EnvironmentRemote, often part of a data teamRemote, typically individual tasks
Industry UsageUsed across AI, machine learning, and data science companiesCommon in AI training data preparation
Job FocusLabeling and categorizing data for machine learningAnnotating data with labels or tags

The Remote Data Labeling Analyst and Remote Data Annotator roles are similar, both involving data labeling tasks in a remote setting. The Analyst may have additional responsibilities like quality checks or data management, but both positions require similar skills and are used widely in AI and machine learning industries.

What are popular job titles related to Remote Data Labeling Analyst jobs in Kentucky? For Remote Data Labeling Analyst jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Remote Data Labeling Analyst jobs in Kentucky look for? The top searched job categories for Remote Data Labeling Analyst jobs in Kentucky are:
What cities in Kentucky are hiring for Remote Data Labeling Analyst jobs? Cities in Kentucky with the most Remote Data Labeling Analyst job openings:
Remote Data Labeling Analyst jobs near you
Infographic showing various Remote Data Labeling Analyst job openings in Kentucky as of June 2026, with employment types broken down into 2% As Needed, 83% Full Time, 10% Part Time, and 5% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Freelance Technical Consultant

Toloka

Remote

Other

Re-posted 2 days ago

Job description

Company Intro

At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains-from doctors and lawyers to physicists and engineers-and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages. We are a well-funded startup with an enviable portfolio of clients including Anthropic, Amazon, Microsoft, Poolside, Recraft,  and Shopify.

Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin, CTO of Shopify  and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world: USA, UK, the Netherlands,  Serbia, and more. 

About the Role

Technical consultants play a key role in our company, ensuring top-level delivery of our product, its correct configuration, and the deployment of tailored AI data solutions that meet our customers' needs and deliver an exceptional experience working with us.
As part of this role, you will not only design and implement data labeling pipelines but also act as a trusted technical advisor for our customers - helping them understand their data needs, discover new opportunities, and build scalable AI solutions.
We are looking for a person with more than 3 years of solid technical background, who feels comfortable working in technical environments, solving data-related tasks using Python and AI, and communicating directly with customers. You should be a confident communicator able to engage with both technical and executive stakeholders and collaborate closely with our commercial team.

Responsibilities1. Client Ownership & Communication
  • Act as the primary technical point of contact for customers across technical and executive stakeholders.
  • Lead discovery conversations to deeply understand client goals, problems and quality criteria.
  • Translate client needs into clear, actionable solution designs and delivery plans.
  • Advise customers on best practices in data collection, data quality, evaluation, and model training workflows.
  • Set expectations proactively, communicate progress regularly, and manage risks and trade-offs transparently.
  • Identify expansion opportunities and additional ways Toloka can create value through data and AI solutions.
2. Solution Design & Delivery
  • Design end-to-end data solutions using Toloka's platform, selecting appropriate components, workflows, and quality controls.
  • Configure data labeling components and quality controls, develop user interfaces and AI-driven tooling (e.g. agentic systems, RAGs, synthetic data generation), and integrate them into end-to-end automated pipelines for AI training and evaluation.
  • Run experiments and pilots to validate quality, throughput, and cost assumptions.
  • Lead technical execution during delivery, coordinating internal teams and external stakeholders as needed.
  • Ensure solutions meet agreed quality, performance, and scalability requirements.
3. End-to-End Ownership & Project Management
  • Own delivery outcomes holistically - including technical performance, quality, timelines, and financial efficiency.
  • Monitor key KPIs (e.g. throughput, quality metrics, Gross Margin, Contribution Margin) and act on deviations.
  • Prioritize work based on customer impact and business value.
  • Analyze data to identify failure modes, inefficiencies, and opportunities for improvement.
  • Continuously optimize solutions through iteration, automation, and adoption of new technologies.
  • Troubleshoot delivery, process, or technical issues in collaboration with support, infrastructure, and product teams.
  • Drive solutions toward stable operation with minimal ongoing maintenance.
RequirementsCore Experience
  • Experience as a Solution Engineer, Technical Solutions Engineer, Data Scientist, Data/Systems Analyst, or Technical Project Manager.
  • Proven experience owning projects end-to-end, including scoping, delivery, and stakeholder management.
  • Direct experience working with external customers on technical projects (requirements gathering, delivery, iteration).
Technical Skills
  • Strong Python skills for data manipulation (e.g. NumPy, pandas), natural language processing (e.g. NLTK, spaCy), and building lightweight web services or tools (e.g. FastAPI, Flask).
  • Solid understanding of ML concepts and data workflows; familiarity with LLMs and prompt engineering is a strong plus.
  • Experience designing multi-stage pipelines and complex systems.
  • Understanding of software development fundamentals: version control, testing, MVPs, iterative development etc..
  • Bachelor's or Master's degree in Data Science, ML/AI, Software Engineering, or a related quantitative field such as Physics or Applied Mathematics, with strong analytical foundations.
  • Ability to reason about trade-offs between quality, speed, cost, and scalability.
Communication & Ownership
  • Excellent English communication skills (B2+), with the ability to explain complex technical concepts to non-technical audiences.
  • Confidence working with data engineers, ML engineers, and researchers from leading tech companies.
  • Strong ownership mindset: comfortable being accountable for outcomes, not just tasks.
  • Ability to manage multiple projects in fast-paced, ambiguous environments.
Nice to have
  • Experience with crowdsourcing, expert workflows, or large-scale data labeling.
  • Experience working on ML training, evaluation, or agentic systems.
  • Familiarity with quality frameworks, audits, or data validation pipelines.


[Important Notice] Scam Alert Regarding Fake Job Postings

It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants.Please be aware:

  • Official Communication: Our recruiting team will only contact you from an official "toloka.ai" email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc,  or other personal or seemingly business email accounts.
  • Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process.
  • Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list
What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn.We are taking this matter very seriously and are working with the appropriate parties to resolve it.
Thank you for your vigilance!

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