How is Research Data used?
Zippia reviewed thousands of resumes to understand how research data is used in different jobs. Explore the list of common job responsibilities related to research data below:
- Recorded research data to effectively present and preserve.
- Conduct field interviews and collect research data in support of a Women's Health Intervention Study (WHIS) research study.
- Collected and accurately entered field research data findings so that the data could later be published.
- Compile research data into collaborative log, resulting in updated Explore Chicago website.
- Presented and published research data at a conference of peers and educators.
- Produced research briefs on the results inquiry process Skills Used Research Data analysis
Are Research Data skills in demand?
Yes, research data skills are in demand today. Currently, 2,225 job openings list research data skills as a requirement. The job descriptions that most frequently include research data skills are field researcher, marketing and research director, and marketing research coordinator.
How hard is it to learn Research Data?
Based on the average complexity level of the jobs that use research data the most: field researcher, marketing and research director, and marketing research coordinator. The complexity level of these jobs is challenging.
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What jobs can you get with Research Data skills?
You can get a job as a field researcher, marketing and research director, and marketing research coordinator with research data skills. After analyzing resumes and job postings, we identified these as the most common job titles for candidates with research data skills.
Field Researcher
Job description:
A field researcher is tasked to directly observe people while living in specific areas. They document and record their observations in order to assist with research. They visit a wide range of localities to study subjects and analyze what causes certain behaviors. They check for completeness of the data acquired and for its accuracy. They also create surveys where chosen respondents answers, and this aids in the more precise outcome of the research.
- Research Data
- GPS
- Data Entry
- Public Health
- Data Collection
- In-Person Interviews
Marketing And Research Director
- Market Research
- Research Data
- Research Findings
- Research Projects
- Primary Research
Marketing Research Coordinator
- Market Research
- Analyze Data
- Marketing Campaigns
- Research Data
- Research Projects
- Press Releases
Research Aide
Job description:
Research aides are professionals who are responsible for assisting professionals in carrying out tasks related to research. These research aides must assist their staff members and clients in designing and executing research projects as well as analyze the project's massive amount of data sets. They are required to conduct data collection while managing them to ensure the accuracy and completeness of data for easy access. Research aides must also perform basic and complex laboratory procedures together with lab technicians as well as design research experiments.
- Data Collection
- Data Entry
- Lab Equipment
- Laboratory Equipment
- Research Data
- Animal Handling
Data Assistant
Job description:
A data assistant's role is to perform support tasks in data management procedures. Their responsibilities often revolve around coordinating with different departments to gather data, maintaining and updating databases, processing and organizing documentation, preparing progress reports, and analyzing data as needed. They may also participate in devising strategies to optimize data management operations. Furthermore, a data assistant must also monitor the operations of databases, performing regular maintenance checks, and reporting to the information technology department should there be any issues and concerns.
- Data Entry
- Data Collection
- Patients
- Data Management
- Research Data
- Access Database
Research Laboratory Technician
Job description:
Research laboratory technicians play a vital role in scientific laboratories. They perform varied duties and responsibilities, which include setting up, operating, and maintaining the laboratory equipment, assisting in laboratory-based research activities such as sampling, testing, and analyzing results, and providing technical support to the laboratory team members. In addition, they are expected to support the development and advancement of science and modern medicine. Other typical duties of research laboratory technicians include preparing samples and specimens, keeping abreast with current technical developments, and ensuring strict compliance with safety procedures.
- Patients
- Chemistry
- Laboratory Equipment
- Cell Culture
- Research Data
- Research Projects
How much can you earn with Research Data skills?
You can earn up to $25,347 a year with research data skills if you become a field researcher, the highest-paying job that requires research data skills. Marketing and research directors can earn the second-highest salary among jobs that use Python, $96,935 a year.
| Job Title | Average Salary | Hourly Rate |
|---|---|---|
| Field Researcher | $25,347 | $12 |
| Marketing And Research Director | $96,935 | $47 |
| Marketing Research Coordinator | $57,307 | $28 |
| Research Aide | $32,225 | $15 |
| Data Assistant | $34,431 | $17 |
Companies using Research Data in 2025
The top companies that look for employees with research data skills are U.S. Department of the Treasury, Pwc, and White Cap Construction Supply Inc. In the millions of job postings we reviewed, these companies mention research data skills most frequently.
| Rank | Company | % Of All Skills | Job Openings |
|---|---|---|---|
| 1 | U.S. Department of the Treasury | 22% | 3 |
| 2 | Pwc | 13% | 18,723 |
| 3 | White Cap Construction Supply Inc | 10% | 670 |
| 4 | PAM Health | 7% | 868 |
| 5 | American Heart Association | 5% | 318 |
4 courses for Research Data skills
1. Data Science for Health Research
In Data Science for Health Research, learn to organize and visualize health data using statistical analysis in programs like R. Explore how to translate data, interpret statistical models, and predict outcomes to help make data-informed decisions within the public health field...
2. How to Visualize Research Data in Tableau
Publishing research often requires the preparation of visual elements like charts, tables, and graphs to better explain the text in a research report. Creating these elements can be done easily and effectively in Tableau. Using Tableau, large and small data sets can be visualized with precision, creativity, interactivity, and options in Tableau. After taking this course learners will know how to create a table, a geovisualization, and a pie chart. Three of the most common research visualizations available. The learners will also learn how to upload data, how to export these tables, and how to incorporate charts and graphs in research reports. Researchers from students to professionals will benefit from learning how to create visualizations based on surveys, observations, experiments, and other types of research methods. Knowledge of research is useful but not required for this project...
3. SPSS Data Analysis for Beginning Researchers
Thank you for checking in SPSS Data Analysis for Beginning Researchers. Who is this course for?As the title implies, this course is for people working on their very first research projects (i. e. beginners / newbies), including but not limited to: Students working on their research papers or dissertationsBeginning researchers with a non-technical backgroundAnyone curious about data analysisWhat is so difficult about data analysis?Many people find data analysis difficult, and with good reasons. Data analysis is difficult because it is not a single discipline. It is multi-disciplinary, which means that it requires integrated knowledge from different fields in order to do it right. Specifically, to conduct data analysis for your research you need: Knowledge in the data analysis software (e. g. SPSS, Excel, R, etc.)Knowledge in statistics conceptsKnowledge in research methodsExperience and skills working with dataWhat you need is not only knowledge in separate fields, but also experience and skills integrating these knowledge together to deal with real life data. However, beginning researchers, by definition, have very little of these knowledge, experience, and skills. For example: You may know how to use the data analysis software, but you don't know what method of analysis to use because you are not familiar with the statistics concepts. You may know some statistics, but you may not know how to calculate the statistics on the computer. You may have knowledge in both statistics and data analysis software, but you are not sure what analysis to conduct in order to fulfill the research needs. You may have knowledge in statistics, software, and research, but you may not have the experience in actually handling data, and you are stuck dealing with practical issues here and there (such as missing and invalid data). There are plenty of textbooks in these different disciplines, but few of them could teach you all these knowledge and skills. The problem is not lack of information. Quite the contrary, the problem is overwhelmingly rich information, so rich that you may not know where to start and how to select, so rich that you may not know how to put them into practice to fulfill your specific needs. How may this course help?This course is designed to be concise and practical. I am not attempting to tell you everything about statistics, SPSS, data analysis, and research - that would make your learning journey unnecessarily difficult. Instead, I am going to guide you, in an structured and practical way, through the minimal set of knowledge and skills you would need to analyze your own data. This course will not make you an expert in statistics, SPSS, data analysis, and research, but it will help you finish your own data analysis. This is to be achieved by the following: Background knowledge. Each section of the course begins with a brief introduction to the minimal set of necessary statistics concepts you need. Practical demonstrations. All the videos are example-based. In each video, I show you how to conduct a practical data analysis task. These tasks are carefully selected from a list of most common analyses that you are likely to conduct. Experience sharing. In addition to statistics and SPSS, I also share a lot of my own experience doing research and data analysis, including how to deal with the most common issues while working with data, avoid the common mistakes and misunderstandings, and work around some annoying bugs in SPSS. Key points. Key points are highlighted throughout the video and also recapped at the end of the videos. Exercise. There is an exercise at the end of each section. This helps you apply what you have learned in the previous videos. There are also questions that prompt you to think deeper about what you are doing. The exercise problems have been used for a few years in my own offline classes so they are proven to be helpful to students. While appropriate, a separate video is dedicated to demonstrating the answers to these exercise problems. References. For those who would like to dig deeper into the statistics concepts, I have included links to useful references for your pursue. So, how may I learn effectively in this course?You may do the following for each section: Watch the videos. Take notes while necessary. Complete the exercise on your own. Knowing is not enough. We must apply! If you forget some of the details, refer back to the previous videos. After attempting the exercise, watch the next video for answers. Watch my steps carefully and compare with yours. In case of any difference, ask yourself which way is better, and why. Last but not least, apply the techniques to your own data. That's all for the introduction. Happy learning!...
4. Data-Driven Customer Research: Unlock Business Success
Unlock the full potential of your business by mastering customer research and data-driven decision making in this comprehensive course! Become a top-notch professional by understanding your customers better and making informed decisions to propel your business forward. To succeed in today's competitive market, understanding your customers' needs, wants, goals, and pain points is crucial. Failing to conduct proper customer research, interviewing the wrong people, or misinterpreting experiment results can lead to poor sales, negative reviews, and even product failure. On the other hand, taking a holistic approach based on science and best practices will help you maximize the value delivered to your customers, resulting in business success. Welcome to Customer Research & Data-Driven Decision Making, the second course in the Product Owner Academy series. In this course, we will take a deep dive into the world of customer research, statistics, user testing, and data-driven decision making. You don't need any prior knowledge of the subject, as we will start from the basics and build up to advanced concepts. What will you learn?Learn cutting-edge techniques in customer research that help you uncover valuable insights and hidden opportunities. Transform your business strategies with data-driven decision making, backed by powerful analysis tools and frameworks. Explore the art of asking the right questions to gather crucial data and ensure the accuracy and reliability of your research. Master industry-leading research methodologies, such as surveys, interviews, and focus groups, to gain a competitive edge. Optimize your business strategies and marketing efforts by understanding customer behavior, preferences, and pain points. This course includes many activities using Miro (a free online whiteboard tool), knowledge tests, and practical examples and advice on how to apply new skills and knowledge in practice. You will also have access to downloadable materials and useful links to maximize your learning outcomes. Who is this course for?Entrepreneurs and small business owners looking to make better decisions and grow their businessProduct managers and marketers seeking to improve product offerings and marketing strategiesAnalysts and data professionals aiming to enhance their customer research and decision-making skillsAspiring researchers and consultants who want to excel in their careers with a solid foundation in customer researchAbout your instructor: I am the founder of Agile Apothecary, an Agile Coach, and Product Owner who has worked with Rakuten, Indeed, and McKinsey & Company. I have been part of Agile transformations across multiple industries and geographies, supported hundreds of teams, and trained thousands of people in my over ten years of professional experience. I am especially passionate about training Product Owners as this role is critical for business success and is as challenging as it is exciting. Don't wait any longer. Sign up today and start your journey towards becoming a skilled and successful customer researcher and data-driven decision-maker!...