What is Data Collection?
Data collection means to analyze and collect all the necessary information. It helps in carrying out research and in storing important and necessary information. The most important goal of data collection is to gather the information that is rich and accurate for statistical analysis.
How is Data Collection used?
Zippia reviewed thousands of resumes to understand how data collection is used in different jobs. Explore the list of common job responsibilities related to data collection below:
- Promoted from Collections Specialist II to Data Collection Specialist a move that allowed more decision making and project management responsibility.
- Collect selected inventory in various stores showing product placement and quantity for manufacturers through data collection and photo imagery.
- Planned and implemented a menu driven system that revolutionized real-time data collection from eight nationally located calling centers.
- Operate manufacturing machinery * Assembling medical devices and documenting progress * Perform data collection duties as stated above
- Make Calls to Data Collection Specialist and/or medical facility for clarification of information if necessary.
- Contacted local and national businesses and individuals conducting telephone data collections regarding various assigned topics.
Are Data Collection skills in demand?
Yes, data collection skills are in demand today. Currently, 43,437 job openings list data collection skills as a requirement. The job descriptions that most frequently include data collection skills are data collection specialist, semiconductor manufacturing technician, and sustainability coordinator.
How hard is it to learn Data Collection?
Based on the average complexity level of the jobs that use data collection the most: data collection specialist, semiconductor manufacturing technician, and sustainability coordinator. The complexity level of these jobs is basic.
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What jobs can you get with Data Collection skills?
You can get a job as a data collection specialist, semiconductor manufacturing technician, and sustainability coordinator with data collection skills. After analyzing resumes and job postings, we identified these as the most common job titles for candidates with data collection skills.
Data Collection Specialist
Job description:
A Data Collection Specialist manages and collects the outstanding accounts receivables from customers and clients. Data Collection Specialists perform various duties that include monitoring all accounts daily, investigating historical data for receivables and debts, and processing refunds and payments. They also collaborate with data analysts to create presentations and surveys, write reports. Other duties include resolving customer credit issues, updating and recording accounts' status, and following up with clients on their overdue payments.
- Data Collection
- Computer Database
- Data Entry
- Outbound Calls
- Telephone Interviews
- Authorization Forms
Semiconductor Manufacturing Technician
- Data Collection
- RF
- Lean Manufacturing
- Etching
- Metrology
- SPC
Sustainability Coordinator
Job description:
A sustainability coordinator helps an organization achieve its goals when it comes to sustainability and being environmentally friendly. It is their duty to develop and support environmental programs and implement its policies and regulations in an effort to reduce environmental damages brought by an organization's operations. Moreover, they must gather and analyze data to identify which areas need improvement, conduct research to determine the ideal practices to attain sustainability, produce progress reports, and implement solutions against problem areas in adherence to the company's vision and mission.
- Data Collection
- Employee Engagement
- Composting
- STARS
- Sustainability Efforts
- Sustainability Initiatives
Field Scientist
Job description:
The duties of a field scientist depend on one's line of work or industry of employment. In general, their responsibilities typically include conducting studies and scientific research, visiting various sites to observe and gather samples, performing laboratory analyses and experiments, maintaining records of all operations, and coming up with conclusions from the research findings. When it comes to employment opportunities, a field scientist may work for learning institutions, government agencies, and private companies, where they usually work together with other scientists and experts.
- Field Testing
- Data Collection
- Geotechnical
- Asbestos
- Storm Water
- EPA
Hydrology Technician
- Data Collection
- Surface Water
- Hydrologic Data
- USGS
- Water Quality Data
- Water Quality Samples
Soil Scientist
Job description:
A soil scientist analyzes soil structures. They research soil's chemical properties, microorganism content, and physical composition. They provide advice on fertilizers, pesticides, and chemical treatments. They also provide advice on the crops best suited for a given soil type.
- GPS
- Data Collection
- GIS
- EPA
- Technical Assistance
- Soil Properties
Conservation Specialist
- Data Collection
- GIS
- Water Quality
- Management Practices
- ArcMap
- Technical Assistance
Geophysicist
Job description:
A Geophysicist studies the Earth's physical properties. They also examine the effects of the atmosphere on radio and satellite communications.
- Data Collection
- Geophysical Data
- C++
- MATLAB
- Data Analysis
- Reservoir Characterization
Residential Trainer
- Developmental Disabilities
- Data Collection
- Independent Living
- Meal Preparation
- Medication Administration
- Doctor Appointments
Senior Hydrogeologist
- Data Collection
- OSHA
- Regulatory Agencies
- Groundwater Flow
- Technical Support
- Geotechnical
Mapping Technician
Job description:
A mapping technician helps cartographers and photogrammetrists produce and update maps. Their work is done using computers and drones, so this position requires familiarity with mapping tools. Their responsibilities are collecting the information to complete maps and surveys, calculating map making information from collected notes, drawing topographical maps, verifying maps, and developing information databases that contain geographic and topographic data. They are also responsible for determining the scales, line sizes and colors to be used for the hard copies of computerized maps.
- GIS
- Data Collection
- Spatial Data
- GPS
- Computer Programs
- Survey Data
Field Crew Chief
- GPS
- Data Collection
- Construction Layout
- Survey Equipment
- Construction Projects
- GIS
Social Scientist
Job description:
A social scientist conducts studies and spearheads research projects that focus on society and human behavior. Although the extent of their responsibilities varies upon their industry or institution of employment, it usually includes planning procedures according to research requirements, identifying and coordinating with research subjects, conducting surveys and interviews, and gathering and analyzing various data. Through the findings of their research, a social scientist generates conclusions and recommendations that will determine or support future efforts. When it comes to employment, a social scientist may work for government agencies, private companies, facilities, or even become an instructor at learning institutions.
- Statistical Analysis
- Data Collection
- Social Science Research
- Data Analysis
- Communicate Research Findings
- Quantitative Data
Lead Field Technician
Job description:
The Lead Field Technician serves as the assistant of the Field Supervisor. Their responsibility includes taking immediate action and making decisions for instances that individuals or organizations need their help. They are the one who implements and monitors a company's guidelines and policy and maintains the standard procedure of all the systems. Also, being an assistant, they can act as an overseer to determine the employees and equipment types that need to work smoothly and orderly.
- Customer Service
- Data Collection
- GPS
- Technical Support
- Preventative Maintenance
- Fiber Optic
Drive Test Engineer
Job description:
For cars and other automobiles' best performance, drive test engineers can be asked for suggestions. From their expertise, one can ensure that the chosen car is equipped with the necessary accessories such as GPS, Bluetooth hubs, an air conditioner, locks, and USB ports. They train and teach people how to drive safely, following road laws and protocols. They monitor for enhancements and provide reports to stakeholders and managers for its application. They can troubleshoot minor software problems in automobiles.
- Data Collection
- GPS
- Pre
- LTE
- E911
- Data Throughput
How much can you earn with Data Collection skills?
You can earn up to $43,904 a year with data collection skills if you become a data collection specialist, the highest-paying job that requires data collection skills. Semiconductor manufacturing technicians can earn the second-highest salary among jobs that use Python, $33,263 a year.
Job Title  | Average Salary | Hourly Rate |
|---|---|---|
| Data Collection Specialist | $43,904 | $21 |
| Semiconductor Manufacturing Technician | $33,263 | $16 |
| Sustainability Coordinator | $52,310 | $25 |
| Scientific Technician | $40,956 | $20 |
| Field Scientist | $76,601 | $37 |
Companies using Data Collection in 2025
The top companies that look for employees with data collection skills are Guidehouse, Deloitte, and Kaiser Permanente. In the millions of job postings we reviewed, these companies mention data collection skills most frequently.
| Rank | Company | % Of All Skills | Job Openings |
|---|---|---|---|
| 1 | Guidehouse | 13% | 1,800 |
| 2 | Deloitte | 8% | 19,842 |
| 3 | Kaiser Permanente | 7% | 4,421 |
| 4 | U.S. Department of the Treasury | 7% | 5 |
| 5 | CDM Smith | 7% | 17,762 |
8 courses for Data Collection skills
1. AWS: Data Collection Systems
AWS: Data Collection Systems Course is the first course of the AWS Certified Data Analytics Speciality Specialization. This Course is designed to describe data collection systems and their characteristics in detail. This course is basically divided into three modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 3:30-4:00 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners. Module 1: Data Collection Systems and Data Streams in AWS Module 2: Data Integration Services in AWS Module 3: Data Compression and Transformation in AWS e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming...
2. Survey Data Collection and Analytics
This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains. In six courses, you will learn the basics of questionnaire design, data collection methods, sampling design, dealing with missing values, making estimates, combining data from different sources, and the analysis of survey data. In the final Capstone Project, you’ll apply the skills learned throughout the specialization by analyzing and comparing multiple data sources.\n\nFaculty for this specialisation comes from the Michigan Program in Survey Methodology and the Joint Program in Survey Methodology, a collaboration between the University of Maryland, the University of Michigan, and the data collection firm Westat, founded by the National Science Foundation and the Interagency Consortium of Statistical Policy in the U.S. to educate the next generation of survey researchers, survey statisticians, and survey methodologists. In addition to this specialization we offer short courses, a summer school, certificates, master degrees as well as PhD programs...
3. Data Collection and Processing with Python
This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a “tag recommender” for the flickr photo sharing site. The course is well-suited for you if you have already taken the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). If you are already familiar with Python fundamentals but want practice at retrieving and processing complex nested data from Internet services, you can also benefit from this course without taking the previous two. This is the third of five courses in the Python 3 Programming Specialization...
4. Framework for Data Collection and Analysis
This course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research question, how to turn your research question into measurable pieces, and how to think about an analysis plan. Furthermore this course will provide you with a general framework that allows you to not only understand each step required for a successful data collection and analysis, but also help you to identify errors associated with different data sources. You will learn some metrics to quantify each potential error, and thus you will have tools at hand to describe the quality of a data source. Finally we will introduce different large scale data collection efforts done by private industry and government agencies, and review the learned concepts through these examples. This course is suitable for beginners as well as those that know about one particular data source, but not others, and are looking for a general framework to evaluate data products...
5. Algorithms, Data Collection, and Starting to Code
This course starts you on your journey learning about computational thinking and beginning C programming. If you’d like to explore how we can interact with the world in a rigorous, computational way, and would also like to start learning to program, this is the course for you! You may have heard lots of talk about computational thinking recently, but if you ask 10 different people what it is you’ll probably get 10 different answers. Rather than trying to define computational thinking, we’ll just say it’s a problem-solving process that includes lots of different components. In this course, we’ll explore algorithms and data collection. Most people have a better understanding of what beginning C programming means! You’ll start learning how to develop C programs in this course by writing your first C program; learning about data types, variables, and constants; and honing your C programming skills by implementing a variety of STEM computations. This course doesn't assume you have any previous programming experience, so don't worry if you've never written code before. If that all sounds interesting to you, go ahead and jump into the course! Caution: Beginning (assuming no prior programming knowledge) is not the same as easy (not hard to do). Learning to program IS hard to do, especially since the courses in this specialization are built from a freshman-level college course. Meeting the course challenges while you master the material will be rewarding to you, but doing that will require hard work and maybe even a few expletives along the way. Module 1: Learn about algorithms and write your first C program Module 2: Discover how we store data in our programs Module 3: Explore how we use data collection to solve problems and answer questions Module 4: Practice writing C programs to implement STEM computations...
6. Teaching Impacts of Technology: Data Collection, Use, and Privacy
In this course you’ll focus on how constant data collection and big data analysis have impacted us, exploring the interplay between using your data and protecting it, as well as thinking about what it could do for you in the future. This will be done through a series of paired teaching sections, exploring a specific “Impact of Computing” in your typical day and the “Technologies and Computing Concepts” that enable that impact, all at a K12-appropriate level. This course is part of a larger Specialization through which you’ll learn impacts of computing concepts you need to know, organized into 5 distinct digital “worlds”, as well as learn pedagogical techniques and evaluate lesson plans and resources to utilize in your classroom. By the end, you’ll be prepared to teach pre-college learners to be both savvy and effective participants in their digital world. In this particular digital world (personal data), you’ll explore the following Impacts & Technology pairs -- Impacts (Show me what I want to see!): Internet Privacy, Custom Ads, Personalization of web pages Technologies and Computing Concepts: Cookies, Web vs Internet, https, Web Servers Impacts (Use my data…. But protect it!): Common Cybersecurity knowledge levels, ISP data collection, Internet design, finding out what is known about you online, software terms and services Technology and Computing Concepts: DNS, Cryptography (ciphers, hashing, encryption, SSL), Deep and Dark Web Impacts (What could my data do for me in the future?): What is Big Data, Machine Learning finds new music, Wearable technologies. Technology and Computing Concepts: AI vs ML, Supervised vs Unsupervised learning, Neural Networks, Recommender systems, Speech recognition In the pedagogy section for this course, in which best practices for teaching computing concepts are explored, you’ll learn how to apply Bloom’s taxonomy to create meaningful CS learning objectives, the importance of retrieval-based learning, to build learning activities with online simulators, and how to use “fun” books to teach computing. In terms of CSTA K-12 computer science standards, we’ll primarily cover learning objectives within the “impacts of computing” concept, while also including some within the “networks and the Internet” concepts and the “data and analysis” concept. Practices we cover include “fostering and inclusive computing culture”, “recognizing and defining computational problems”, and “communicating about computing”...
7. Develop Mobile Data Collection Solutions using Kobo Toolbox
More organizations than ever before are embracing the switch from data collection using paper forms to using mobile devices. This is so due to the benefits of mobile data collection that include better data quality, speed and convenience, as well as being low cost. One of the best platforms for developing and deploying mobile data collection forms is Kobo Toolbox. The platform which includes a mobile app for data collection and web based tools for developing forms, aggregating data, managing data, and data visualizations, is by far the most feature rich and can be used throughout an organization's data management cycle. By the end of the course, participants will be able to:- Develop a data collection form in Kobo Toolbox- Implement skip and validation logic- Deploy the form into mobile devices- Collect and upload data- View and download data- Visualize data using reports and maps...
8. Mobile GIS data collection apps with Leaflet and PostGIS
Learn how to develop your own HTML5 GPS data collection applications that work like a native app on your mobile device. While there are many canned options available for mobile data collection that may meet your needs, there are many times when it may be more cost-effective to develop your own. Cost - Even if your needs are simple many commercial applications require monthly per-user subscriptions, often in the neighborhood of $30-$50 per month. For 1 or 2 users that may not be much but with 50 users it quickly becomes cost effective to write your own. Customizability - Commercial non-programming solutions tend to be one-size fits all. Although they may have some flexibility, it is not uncommon for many applications to need functionality that is not available. Writing your own mean that if you can envision it you can implement it. Often you can implement it faster than you could in a non-programming solution even if it is available. Real-time data access - The techniques taught in this course access a PostGIS database directly so that any changes that are made are available immediately to any other client applications whether they be desktop GIS like ArcGIS or QGIS, other web applications, or other client software such as a spreadsheet program, etc. This also means that there is no time wasted transferring data from device to server, etc which may save hundreds or even thousands of man hours in large data gathering efforts and avoid a large source of errors. HTML5 web applications also have some downsides for this type of work and these are discussed in the course and potential solutions are also addressed...