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Data Collection Jobs in Georgia (NOW HIRING)

Retail Data Collection Associate - PT

Statesboro, GA · On-site

$12.50 - $14.25/hr

Equal Opportunity Employer As a retail data collection associate, you would be a part of our CROSSMARK Field Intelligence Team. The primary function of this team is to travel locally to grocery, mass ...

Retail Data Collection Associate - PT

Statesboro, GA · On-site

$12.50 - $14.25/hr

Equal Opportunity Employer As a retail data collection associate, you would be a part of our CROSSMARK Field Intelligence Team. The primary function of this team is to travel locally to grocery, mass ...

Develop, maintain, and document procedures for data collection, database management, and analysis (including development of analytic plans as directed by the COR). * Develop guidance documents and ...

Automate the data collection process * Identify valuable data sources * Present information in an easily digestible format * Collaborate with other teams within the organization * Plans, conducts ...

Our field data collection teams are spread across Europe and North America, ready to accept new challenges. Project objective The goal of the project is to help collect images of streets, main points ...

Our field data collection teams are spread across Europe and North America, ready to accept new challenges. Project objective The goal of the project is to help collect images of streets, main points ...

Company description Service Measure (SM) is a field data collection company founded in 2013 in New York. We collect data where automation is not possible. We count features, take pictures, make ...

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Data Collection information

See Georgia salary details

$13

$21

$26

How much do data collection jobs pay per hour?

As of May 28, 2026, the average hourly pay for data collection in Georgia is $21.37, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $21.92 per hour, depending on experience, location, and employer.

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

To thrive as a Data Collection Specialist, you need strong analytical abilities, attention to detail, and a background in statistics or data management, often supported by a relevant degree or coursework. Familiarity with data collection tools like survey platforms, Excel, and database management systems, as well as knowledge of data privacy regulations, is essential. Strong organizational skills, clear communication, and adaptability help ensure accuracy and efficiency in gathering and recording data. These skills are crucial for collecting reliable data that supports informed decision-making and organizational objectives.

What are some common challenges faced by professionals in data collection roles, and how can they be overcome?

Data collection professionals often encounter challenges such as ensuring data accuracy, managing large volumes of data, and maintaining data privacy. Inaccurate or incomplete data can compromise analysis, so attention to detail and robust validation processes are essential. Additionally, collaborating closely with other team members, such as analysts and IT staff, helps streamline workflows and troubleshoot issues quickly. Staying updated on best practices and using reliable tools can further improve efficiency and data quality.

What is data collection?

Data collection is the process of gathering and measuring information on targeted variables in a systematic way to answer research questions, test hypotheses, or evaluate outcomes. It is a critical first step in research, analytics, and decision-making, ensuring that the data collected is accurate, reliable, and relevant. Data collection can be done through various methods, including surveys, interviews, observations, or digital tools, depending on the objectives and resources available. Proper data collection enables organizations and researchers to make informed decisions based on evidence and trends.

What is the difference between Data Collection vs Data Analyst?

AspectData CollectionData Analyst
Required CredentialsHigh school diploma or equivalent; some roles may require certifications in data toolsBachelor's degree in data science, statistics, or related field; certifications like SQL or Python often preferred
Work EnvironmentFieldwork, surveys, online data gathering, or office-based data entryOffice setting, analyzing data sets, creating reports
Employer & Industry UsageResearch firms, marketing agencies, government agenciesTech companies, finance, healthcare, consulting firms
Common Search & Comparison IntentUnderstanding data collection methods and rolesAnalyzing data to derive insights and support decision-making

Data Collection involves gathering raw data through various methods, while Data Analysts interpret and analyze that data to generate insights. Both roles are essential in data-driven industries but focus on different stages of the data process.

What are the most commonly searched types of Data Collection jobs in Georgia? The most popular types of Data Collection jobs in Georgia are:
What are popular job titles related to Data Collection jobs in Georgia? For Data Collection jobs in Georgia, the most frequently searched job titles are:
What cities in Georgia are hiring for Data Collection jobs? Cities in Georgia with the most Data Collection job openings:
Infographic showing various Data Collection job openings in Georgia as of May 2026, with employment types broken down into 2% As Needed, 66% Full Time, 17% Part Time, 2% Temporary, 11% Contract, and 2% Nights. Highlights an 87% In-person, 2% Hybrid, and 11% Remote job distribution, with an average salary of $44,448 per year, or $21.4 per hour.
Data Collection Supervisor, Self-Driving

Data Collection Supervisor, Self-Driving

Tesla

Atlanta, GA • On-site

Full-time

Posted 28 days ago


Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers


Job description

Job Summary:
Tesla is seeking a high intensity action-oriented leader to accelerate their vehicle-level testing by supporting and coordinating local operations. The Data Collection Supervisor will be responsible for maintaining excellent data collection through management of a team of vehicle operators and individual contributions to testing tracks.
Responsibilities:
• Be an expert in self-driving concepts with the ability to track data deeply, train drivers across various testing tracks, and provide constructive feedback to the team
• Personally contribute to the AI dataset through your own testing and data collection
• Plan data collection targets for each week and measure progress
• Audit teams’ clips to ensure excellent performance, coach drivers when improvement is needed, and conduct weekly ride-alongs with drivers to ensure quality
• Review/approve timecards, expense reports, travel requests, and schedule shifts for Vehicle Operators
• Support building education materials for data tracks (quizzes, videos, documents), as needed
Qualifications:
Required:
• Valid driver's license and minimum 3 years of driving history required
• Ability to work a flexible schedule; on-call during off shifts for escalations
• Experience managing and motivating hourly teams. Fair leadership, ensuring balance between building good team culture and pushing team toward excellence to prioritize team success
• Excellent computer skills, in particular a working knowledge and familiarity with MacOS, Linux, and Windows, as well as strong MS Office skills
• Ability to navigate and thrive in ambiguous environments
• This is a safety sensitive position which is subject to drug testing requirements per Tesla policy and in accordance with applicable law
Preferred:
• Familiarity with testing AI-based products and/or building Datasets for AI a plus
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

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