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Remote Data Labeling Analyst Jobs in Detroit, MI

Integrating heterogeneous enterprise datasets into structured, analysis-ready pipelines using ... Benefit Summary This role is remote but if you live within 50 miles within Dearborn, MI, you will ...

Analyze usage data and feedback to inform product enhancements and innovation strategies. * Support the development of new tools and platforms (e.g., PowerApps, SharePoint, Power BI) for project ...

Privacy Analyst (Remote)

Dearborn, MI · Remote

$85K - $100K/yr

Support Data Subject Access Request (DSAR) processes and privacy-related issue resolution * Ensure ... Strong analytical and problem-solving skills * Knowledge of privacy regulations such as CCPA and ...

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Remote Data Labeling Analyst information

See Detroit, MI salary details

$33.7K

$81.8K

$134.6K

How much do remote data labeling analyst jobs pay per year?

As of Aug 8, 2026, the average yearly pay for remote data labeling analyst in Detroit, MI is $81,811.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,900.00 and $96,000.00 per year, depending on experience, location, and employer.

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 Detroit, MI? The most popular types of Data Labeling Analyst jobs in Detroit, MI are:
What job categories do people searching Remote Data Labeling Analyst jobs in Detroit, MI look for? The top searched job categories for Remote Data Labeling Analyst jobs in Detroit, MI are:
What cities near Detroit, MI are hiring for Remote Data Labeling Analyst jobs? Cities near Detroit, MI with the most Remote Data Labeling Analyst job openings:

Analyst 2, Data Analytics & Business Intelligence

Comcast

Plymouth, MI • On-site, Remote

Full-time

Posted 16 days ago


Job description

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast.

Job Summary

This job works closely with stakeholders to define data needs, develop models, and extract actionable insights for informed decision-making. It leverages advanced analytics and big data platforms to predict trends and measure business performance. The role also upholds data governance standards to ensure quality and compliance in analytics.

Job Description

This position is an in-office role 4 days a week and 1 day remote.

Responsibilities:

AI-Driven Forecasting & Planning

  • Lead the development and implementation of AI-enabled forecasting solutions.
  • Apply machine learning, predictive analytics, and scenario modeling to improve forecast accuracy and business planning.
  • Design and maintain rolling forecast frameworks that automatically incorporate changing business conditions.
  • Drive automation of forecast updates, assumptions management, variance analysis, and reporting.

Budget & Financial Performance Optimization

  • Modernize budget development and forecasting processes through automation and AI.
  • Develop intelligent models that identify risks, opportunities, and performance drivers.
  • Create automated budget allocation and investment optimization frameworks.
  • Support long-range planning through advanced business and financial modeling.
  • Improve planning cycle speed while enhancing transparency and accountability.

Performance Management Transformation

  • Build AI-driven performance management capabilities that identify trends, opportunities, and operational risks.
  • Create automated scorecard generation and target-setting processes.
  • Develop predictive performance indicators to proactively identify areas requiring intervention.
  • Leverage AI to generate actionable insights, coaching recommendations, and operational guidance.
  • Design frameworks that connect operational metrics, incentive programs, and financial outcomes.

Process Automation & Efficiency

  • Evaluate and redesign complex business processes to eliminate manual activities.
  • Deploy AI agents, workflow automation, and self-service analytics solutions.
  • Reduce cycle times for forecasting, budgeting, reporting, and business reviews.
  • Standardize tools, methodologies, and operating procedures.
  • Establish measurable efficiency targets and track realized value.

Advanced Analytics & Modeling

  • Develop predictive, prescriptive, and scenario-based models to support strategic decisions.
  • Create simulations and sensitivity analyses to evaluate business opportunities and risks.
  • Translate complex analytics into executive-ready recommendations.

Strategic Leadership

  • Partner with Finance, Operations, Technology, and Executive Leadership to identify high-value AI opportunities.
  • Collaborating with business leaders to discern data requirements and crafting technical specifications for analytics
  • Evaluating data relevance, sourcing alternatives, and ensuring robust analytics for stakeholder inquiries
  • Employing self-service tools to analyze complex datasets, extracting actionable business insights
  • Querying diverse big data platforms, including Teradata, SQL Server, Hadoop, and AWS, for comprehensive analysis
  • Merging datasets from varied sources to support thorough business analysis
  • Conducting exploratory data analysis, hypothesis testing, and pinpointing key business drivers
  • Developing predictive models for sales, demand, and other vital business metrics
  • Assessing campaign outcomes, measuring effectiveness, and pinpointing enhancement opportunities
  • Ensuring compliance with data governance policies and standards across analytics practices
  • Consistent exercise of independent judgment and discretion in matters of significance.
  • Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary.
  • Other duties and responsibilities as assigned.

Employees at all levels are expected to:

  • Understand our Operating Principles; make them the guidelines for how you do your job.
  • Own the customer experience think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services.
  • Know your stuff be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences.
  • Win as a team make big things happen by working together and being open to new ideas.
  • Be an active part of the Net Promoter System a way of working that brings more employee and customer feedback into the company by joining huddles, making call backs and helping us elevate opportunities to do better for our customers.
  • Drive results and growth.
  • Support a culture of inclusion in how you work and lead.
  • Do what's right for each other, our customers, investors and our communities.

Skills

Actionable Insights, Analytics, Business Operations, Data Forecasting

Compensation

This job can be performed in Colorado, Illinois, and Minnesota with a Pay Range of $66,115.55 - $109,090.66Comcast intends to offer the selected candidate base pay within this range, dependent on job-related, non-discriminatory factors such as experience. The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later.

Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That's why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality - to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details.

Education

Bachelor's DegreeWhile possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.

Certifications (if applicable)

Relevant Work Experience

2-5 YearsComcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.