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Job outlook for analytical data miners in the United States
Are analytical data miner jobs in demand?
Analytical data miner job and salary trends over time
Analytical data miner jobs over time
Analytical data miner job growth rate over time
| Year | # of jobs | % of population |
|---|---|---|
| 2021 | 98 | 0.00% |
| 2020 | 93 | 0.00% |
| 2019 | 90 | 0.00% |
| 2018 | 45 | 0.00% |
| 2017 | 37 | 0.00% |
Average analytical data miner salary over time
Analytical data miner salary by year
| Year | Avg. salary | Hourly rate | % Change |
|---|---|---|---|
| 2026 | $83,793 | $40.29 | +3.4% |
| 2025 | $81,032 | $38.96 | +2.3% |
| 2024 | $79,198 | $38.08 | +2.0% |
| 2023 | $77,654 | $37.33 | +2.3% |
| 2022 | $75,899 | $36.49 | +1.5% |
Analytical data miner jobs by state
Most common states for analytical data miners
| Rank | State | Population | # of jobs | Employment/ 1000ppl |
|---|---|---|---|---|
| 1 | District of Columbia | 693,972 | 374 | 54% |
| 2 | Massachusetts | 6,859,819 | 1,376 | 20% |
| 3 | New Hampshire | 1,342,795 | 197 | 15% |
| 4 | Connecticut | 3,588,184 | 485 | 14% |
| 5 | Alaska | 739,795 | 102 | 14% |
| 6 | Maryland | 6,052,177 | 803 | 13% |
| 7 | Minnesota | 5,576,606 | 703 | 13% |
| 8 | Delaware | 961,939 | 129 | 13% |
| 9 | North Dakota | 755,393 | 98 | 13% |
| 10 | Illinois | 12,802,023 | 1,490 | 12% |
| 11 | New Jersey | 9,005,644 | 1,082 | 12% |
| 12 | Virginia | 8,470,020 | 1,004 | 12% |
| 13 | Colorado | 5,607,154 | 656 | 12% |
| 14 | Utah | 3,101,833 | 369 | 12% |
| 15 | Montana | 1,050,493 | 128 | 12% |
| 16 | North Carolina | 10,273,419 | 1,137 | 11% |
| 17 | Washington | 7,405,743 | 822 | 11% |
| 18 | Nebraska | 1,920,076 | 215 | 11% |
| 19 | South Dakota | 869,666 | 99 | 11% |
| 20 | Idaho | 1,716,943 | 176 | 10% |
Most common cities for analytical data miners
| Rank | City | # of jobs | Employment/ 1000ppl | Avg. salary |
|---|---|---|---|---|
| 1 | East Hartford | 1 | 2% | $83,350 |
| 2 | Santa Clara | 1 | 1% | $121,349 |
| 3 | Wilmington | 1 | 1% | $83,867 |
| 4 | Minneapolis | 2 | 0% | $84,516 |
| 5 | New York | 2 | 0% | $81,343 |
| 6 | Washington | 2 | 0% | $96,352 |
| 7 | Boston | 1 | 0% | $82,628 |
| 8 | Denver | 1 | 0% | $66,509 |
| 9 | Los Angeles | 1 | 0% | $108,920 |
| 10 | Phoenix | 1 | 0% | $91,534 |
| 11 | San Francisco | 1 | 0% | $121,974 |
| 12 | San Jose | 1 | 0% | $121,169 |
Analytical Data Miner job outlook: Expert opinions
Our panel of analytical data miner experts
Kennesaw State University
Mississippi College
Adelphi University
San Francisco State University
Kennesaw State University
Utah State University
Kettering University
Cumberland University
Texas A&M University
Pennsylvania State University
University of Missouri - St Louis
University of Oregon
Denison University
Idaho State University
What general advice would you give to an Analytical Data Miner?
Dr. Yeol Huh: Avoid falling for the myth of adopting technology just for its own sake. Although it's tempting to experiment with the latest innovations, your approach should be grounded in fundamentals. Begin by defining the goals or outcomes you wish to achieve, and consider relevant theories that guide your approach.
What will help Analytical Data Miners increase their earning potential?
Dr. Yeol Huh: Data literacy is undoubtedly one of the most crucial skills in the field today. Understanding how to identify, collect, analyze data, and make data-driven decisions will be key competencies in the next 3-5 years. This will increasingly include AI literacy, enabling you to identify and apply appropriate AI technologies to your specific contexts.
What Analytical Data Miner skills would you recommend for someone trying to advance their career?
Taylor Poe Ph.D.: Data analysis is certainly a growing field, and we cannot deny the benefits of having some programming skills. The ability to communicate and work with others will open doors to bigger projects.
What general advice would you give to an Analytical Data Miner?
Dr. Shana Caro: Graduates can maximize their salary potential by finding jobs that suit their own strengths, and writing a convincing cover letter that tells hiring managers just how much value they can add to the company. They can also research starting salaries in their chosen career, and negotiate their salaries based on that evidence. Graduates can also consider moving to areas with higher paying jobs. Finally, graduates should consider and ask what criteria their bosses will use when evaluating their work output; essentially, they should find out what matters most to the company or boss, and work hardest on those metrics. There has also been a tension between the graduates' desire for remote work and companies' preference for in-person work. Graduates should consider flexibility in their working arrangements, since how happy your supervisors are with you may determine whether you get raises and promotions. Putting in face time can help you stand out in an increasingly remote world.
What will help Analytical Data Miners increase their earning potential?
Dr. Shana Caro: In the next 3-5 years, graduates will want to have a mix of hard and soft skills. As AI and LLMs become more powerful and prevalent, being able to use these new tools effectively will be incredibly helpful in a variety of industries. Coming up with the right prompts to direct these models is a high-level skill that takes practice. In data science jobs, which Biological and Physical Science majors would excel at, basic computer programming in any language, data visualization, and understanding A-B testing will be important. The value-add of graduates in these majors is frequently that they can translate mathematical results into business insights in plain English and clear data visualizations. Additionally, graduates will also have to focus on their soft skills -- especially communicating with their managers and teammates in a professional and effective manner. Finally, flexibility is a key soft skill in any field. Graduates should be able to take criticism and improve their work, and be excited to learn new technical skills.
Dr. Bob Patterson DNP, MSN, RN
ProfessorSan Francisco State University
Registered Nursing, Nursing Administration, Nursing Research And Clinical Nursing
What general advice would you give to an Analytical Data Miner?
Dr. Bob Patterson DNP, MSN, RN: I would advise graduates starting their career in the field to focus on continuous learning, networking, and gaining practical experience. It's essential to stay updated with the latest trends and technologies in the field to remain competitive.
What Analytical Data Miner skills would you recommend for someone trying to advance their career?
Dr. Bob Patterson DNP, MSN, RN: In the next 3-5 years, skills such as data analysis, digital literacy, and intercultural communication will become increasingly important in the field. Employers are looking for candidates who can adapt to rapidly changing environments and work effectively with diverse teams.
What will help Analytical Data Miners increase their earning potential?
Dr. Pengcheng Xiao: Maximizing salary potential when starting a career in mathematics involves pursuing advanced degrees or certifications, gaining practical experience through internships and research opportunities, acquiring in-demand skills such as programming and data analysis, negotiating effectively for competitive compensation packages, and staying updated with market trends to identify opportunities for career advancement and higher salaries.
What Analytical Data Miner skills would you recommend for someone trying to advance their career?
Polly Conrad: Entering the job market with a degree in Information Systems or Data Analytics can be both exciting and daunting. The landscape of these fields is dynamic, with continuous advancements in technology and methodologies. Here are some key pieces of advice for new graduates:
1. Embrace Lifelong Learning: The tech industry evolves rapidly, and staying relevant requires continuous learning. Engage in professional development opportunities, attend workshops, and earn certifications in emerging technologies and methodologies (Utah State University Graduate Certificates). 2. Network Actively: Building a strong professional network can open doors to job opportunities and career advancements. Attend industry conferences, join professional associations, and leverage platforms like LinkedIn to connect with industry professionals. 3. Seek Mentorship: Finding a mentor can provide invaluable guidance and insights. Mentors can help you navigate your career path, offer advice on skill development, and provide support during challenging times. 4. Gain Practical Experience: Internships, co-op programs, and project-based work can provide hands-on experience that is highly valued by employers (Utah State University Analytics Solutions Center). Practical experience helps you apply theoretical knowledge to real-world problems and enhances your resume.
What will help Analytical Data Miners increase their earning potential?
Polly Conrad: The fields of Information Systems and Data Analytics are continuously evolving, and several skills are expected to become increasingly important over the next 3-5 years:
1. Data Literacy: As data becomes more integral to decision-making, the ability to understand, interpret, and communicate data insights will be crucial. 2. Artificial Intelligence and Machine Learning: Proficiency in AI and ML will be highly sought after, as these technologies drive innovation across various industries. 3. Cybersecurity: With the growing number of cyber threats, skills in cybersecurity will be essential to protect data and ensure the integrity of information systems. 4. Cloud Computing: Expertise in cloud platforms and services will be critical as organizations continue to migrate their operations to the cloud. 5. Soft Skills: Communication, teamwork, and problem-solving skills are always in demand. The ability to work effectively in diverse teams and communicate technical concepts to non-technical stakeholders will set you apart.
What general advice would you give to an Analytical Data Miner?
John Phillips: Gain experience through undergraduate research and seek opportunities that capitalize on the unique skills acquired during laboratory work. Employers highly value new graduates who are already proficient with the instruments and software relevant to their field. Additionally, having experience in a topic aligned with a company's current projects can provide an extra advantage.
What Analytical Data Miner skills would you recommend for someone trying to advance their career?
John Phillips: With the continuous advancement of computational processing power, having a strong grasp of software programming and data analysis becomes progressively more advantageous. The widespread adoption of Machine Learning techniques in various industries has empowered many new companies to tackle chemical problems that were previously deemed too complex.
Dr. Osama Aljarrah
Assistant ProfessorKettering University
Manufacturing Engineering
What Analytical Data Miner skills would you recommend for someone trying to advance their career?
Dr. Osama Aljarrah: As someone who deeply cares about my students' success beyond graduation, I strongly recommend seeking a mentor. Choose someone you respect and whose career path inspires you—whether it's a teacher, manager, or even a family member. A good mentor can offer invaluable guidance and support as you navigate the early stages of your career.
What general advice would you give to an Analytical Data Miner?
Nitesh Saxena: In the near-term, AI and ML are going to very important and highly sought-after skills. To pad along with that, cybersecurity is an essential area to make sure the AI models work the way they should even under the influence of an adversary. Privacy and ethics are not be ignored either as real-world AI must respect people’s privacy and societal boundaries.
What Analytical Data Miner skills would you recommend for someone trying to advance their career?
Nitesh Saxena: The key would be to focus on continuous experiential learning and dynamically adjusting to the changing landscape of this beautiful field.
Dr Paul Milewski
Head, Department of MathematicsPennsylvania State University
Applied Mathematics
What general advice would you give to an Analytical Data Miner?
Dr Paul Milewski: Because mathematics is a universal language of science, engineering, finance and data, Mathematicians can have many jobs. For example, mathematicians working as data scientists produce mathematical models and simulate them on computers in order to explain patterns in data. Mathematicians working in cryptography work in improving digital security by creating and breaking encryptions.
What will help Analytical Data Miners increase their earning potential?
Dr Paul Milewski: Mathematicians end up in such diverse jobs that its hard to generalize. We love the beauty and power of mathematics; we don’t particularly like everyone telling us they hate math!
What Analytical Data Miner skills would you recommend for someone trying to advance their career?
Ambrose Kidd III: Having a broad skill set and being prepared to learn on the job. The highest salaries will be for those that get their foot in the door and then demonstrate critical thinking and leadership skills.
What general advice would you give to an Analytical Data Miner?
Miles Williams: Social science, especially empirical social science, is highly quantitative. Some argue it's an applied area of STEM, with a strong emphasis on data collection, statistics, and hypothesis testing. Many social scientists are using cutting-edge machine learning methods in their research, and some are pushing the boundaries of advanced methods and developing new ones. This isn't always obvious to undergraduates starting out in social science, however. Most programs focus on talking about issues and theories. Some will incorporate a course or two on quantitative data analysis and research design, but such skills are not generally emphasized in the overall curriculum. For some students, this is perfectly fine and even good. Theories and issues are important. But some students with a talent for STEM who would actually find the substance of social science interesting may self-select out of social science programs because the quantitative aspects of the field are minimized. The reverse can also be true, students who prefer the substance but who are less certain of their abilities in STEM (or simply find it uninteresting) may self-select out of STEM, preferring a major in the humanities or social sciences instead. I was actually one of the latter at the undergraduate level. I had a knack for math and science, but by the time I finished high school I didn't find these subjects inherently interesting, but I did care about politics, policy, and moral issues. I didn't realize until I went to grad school that I could actually apply the tools of STEM to my other substantive interests. Not knowing that these two things can go hand-in-hand early on put me at a disadvantage after I graduated. It was really a missed opportunity. As a social scientist, you have the ability to bring both technical skills and substantive domain knowledge to all kinds of societal problems. If you can focus on ways to emphasize how you embody both substance and technique, that is where your comparative advantage lies in a career as a social scientist. So here's my advice: Think about what skills you were able to develop in whatever social science program you went through, and consider whether you're prepared to fully sell yourself as a quantitative social scientist, embodying both solid technical skills in research and data analysis and deep domain knowledge of societal issues and theories. Even if you didn't learn all the relevant quantitative skills in earning your degree, there are many great open source options for learning these skills, and other paid options that allow you to earn a certificate in data science (or some adjacent version of this, like data analytics, etc.).
What Analytical Data Miner skills would you recommend for someone trying to advance their career?
Miles Williams: As I alluded to in the previous response, the quantitative aspects of social science are becoming increasingly important. To be sure, not all social scientists need quantitative skills. Many UX jobs often entail using qualitative research methods and process tracing. However, over the past couple of decades most empirical social scientists have become, effectively, data scientists who happen to specialize in a particular sub-field or issue area. Statistical programming (particularly with Python and R) is therefore a key skill, and it will only grow in importance over the next 3-5 years.
What general advice would you give to an Analytical Data Miner?
Marco Schoen Ph.D.: ((( - that is something I have not figured out - I will leave this one out)))
What Analytical Data Miner skills would you recommend for someone trying to advance their career?
Marco Schoen Ph.D.: Current innovation is often based on the ability to gather data and infer information pertinent to a company's success. Tools that employ data processing, including machine and deep learning, have the potential to transform a company's approach on how data is gathered, processed and utilized. Staying current with these types of tools and knowing their limitations but also recognizing how to utilize these tools to the company's benefit will help employees to be effective contributors and remain attractive to potential employers.