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Remote Data Labeling Analyst Jobs in Connecticut

LOVESAC COMPANY

Sr. Engineer, Data & Analytics

Stamford, CT · Remote

$122K - $146K/yr

This position is remote and will report into Lovesac Corporate HUB based in Stamford, CT ... Manage workspace access, sensitivity labels, and data governance across Fabric and Power BI (e.g ...

Cleaning Contracts

Sales Analyst

Fairfield, CT · On-site +1

$75K - $95K/yr

🔍 About the Role We're seeking a data-driven Sales Analyst with sharp business acumen and a ... Hybrid flexibility (office presence encouraged for collaboration, remote options available)

RTX Corporate

R2R SAP Business Analyst - Remote

Hartford, CT · On-site +1

$52.75 - $70.50/hr

US-CT-REMOTE Position Role Type: Remote U.S. Citizen, U.S. Person, or Immigration Status ... Experience with finance processes including such as Finance Master Data, Allocations, FP&A, ...

Aequor

$115K - $138K/yr

100% Remote Please source at open market rate This is a job template for special exceptions. ABOUT ... Strong business analysis skills, including requirements gathering, process mapping, documentation ...

Quest Global

RFQ Analyst

Windsor Locks, CT · Remote

$29.81 - $34.62/hr

Prepare technical data packages for export (both US and International) * Provide analytics on ... Work Requirements: This position is classified as Remote within the United States. Travel ...

BIC

Category Analyst, Shave

Shelton, CT · Remote

The Category Analyst supports U.S. category development initiatives through data analysis ... Data integrity across customer reporting #LI-remote BIC World is an Equal Opportunity Employer. We ...

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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?

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 the most commonly searched types of Data Labeling Analyst jobs in Connecticut?

The most popular types of Data Labeling Analyst jobs in Connecticut are:

What are popular job titles related to Remote Data Labeling Analyst jobs in Connecticut?

For Remote Data Labeling Analyst jobs in Connecticut, the most frequently searched job titles are:

What job categories do people searching Remote Data Labeling Analyst jobs in Connecticut look for?

The top searched job categories for Remote Data Labeling Analyst jobs in Connecticut are:

What cities in Connecticut are hiring for Remote Data Labeling Analyst jobs?

Cities in Connecticut 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 Connecticut as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Technical Clinical Data Manager /Data Analyst (Remote)

Penfield Search Partners

Fairfield, CT • Remote

Full-time

Posted 14 days ago

Job description

Contact: Neisha Camacho/Terra Parsons -
No 3rd party candidates

We are partnering with a growing biotech organization seeking a Clinical Data Manager/Data Analyst to support ongoing and upcoming clinical programs across multiple therapeutic areas.

This role will sit within a highly collaborative clinical development team and is ideal for a hands-on, analytical Clinical Data Manager who enjoys digging into the data, identifying trends or issues proactively, and developing creative solutions to improve data quality and study execution. The client is seeking someone resourceful and technically curious — not just process-oriented — with the ability to independently explore datasets, generate meaningful reports, and surface potential issues early.

The ideal candidate will bring a blend of traditional clinical data management expertise along with strong data review, querying, and analytical skills. Experience with R, SQL, SAS, or other data interrogation and reporting tools is highly desirable.

Key Responsibilities

  • Support clinical data management activities across studies from start-up through database lock
  • Perform hands-on data review and exploratory analysis to identify data trends, inconsistencies, missing data patterns, and potential study risks
  • Develop custom reports, listings, and data visualizations to support proactive data cleaning and study oversight
  • Utilize R, SQL, SAS, or similar tools to query, analyze, and troubleshoot clinical datasets
  • Partner with CROs and vendors to ensure high-quality, timely data delivery
  • Collaborate cross-functionally with Clinical Operations, Biostatistics, Statistical Programming, Medical, and Safety teams on data review strategies and issue resolution
  • Contribute to development and review of key deliverables including:
    • Data Management Plans (DMPs)
    • eCRF design and completion guidelines
    • Edit checks and query logic
    • User Acceptance Testing (UAT)
    • Data review plans and cleaning processes
  • Support ongoing query management and ensure data integrity, consistency, and inspection readiness
  • Assist with implementation of data standards, reporting enhancements, and process improvements
  • Work independently to investigate data anomalies and recommend practical solutions in a fast-paced biotech environment

Qualifications

  • BS in a scientific, technical, or clinical discipline
  • Approximately 5–8 years of clinical data management experience within biotech, pharma, or CRO environments
  • Strong hands-on experience reviewing and interrogating clinical trial data
  • Experience using R, SQL, SAS, or other querying/reporting tools to analyze clinical data and generate custom reports
  • Experience with EDC systems such as Medidata Rave, Oracle, or Veeva
  • Working knowledge of CDISC standards (SDTM/ADaM) and downstream data usage
  • Experience supporting Phase II and/or III clinical trials; CNS experience is a plus
  • Exposure to CRO/vendor oversight
  • Understanding of clinical data structures and dictionaries including MedDRA and WHODrug
  • Strong critical thinking and problem-solving skills with the ability to work independently
  • Resourceful, proactive, detail-oriented, and comfortable operating in a dynamic biotech environment
  • Strong communication and cross-functional collaboration skills