What does an analytical data miner do?
An analytical data miner specializes in providing analytical services to help organizations make decisions and optimize their daily operations. They may work in the medical, manufacturing, information technology, construction, and finance industries. Although the extent of their responsibilities depends on their place of employment, it typically includes gathering and analyzing data through software and applications, examining statistical information, maintaining records, and presenting detailed reports in adherence to the company's protocols and guidelines, including its policies and regulations.
Analytical data miner responsibilities
Here are examples of responsibilities from real analytical data miner resumes:
- Manage weapon system project websites via SharePoint, including troubleshooting technical issues and developing guidelines for public/private information and user permissions.
- Produce population behavior GIS health risk assessments base demographics, income & medical data.
- Work with carriers to resolve EDI data issues.
- Develop SAS programs for demographic data process in UNIX.
- Train new employees on both SAS programming and data processing perspectives.
- Develop ETL processes and schedule jobs to run on a daily basis.
- Design end-to-end controls for key data handoff points in AML process stream.
- Prepare and maintain an up-to-date written guidance on the data mining process, in word and HTML.
- Work on Linux shell scripts for business processes and with loading the data from different systems to the HDFS.
- Perform regression analysis to evaluate data using pandas, and create a classifier to predict the success of new projects.
- Implement data mining algorithms for Pearson educational data analytics in Matlab.
- Develop server base visualization applications that leverage machine learning and predictive analytic to predictive equipment state.
- Deliver an interactive network visualization framework for quickly responding to and resolving network availability issues and service disruptions.
- Provide metadata management and support, including the enforcement of standards and naming conventions, data normalization and rationalization efforts.
- Create conceptual and logical metadata models to capture enterprise-wide requirements for metadata to be used in implementing a corporate metadata solution.
Analytical data miner skills and personality traits
We calculated that 12% of Analytical Data Miners are proficient in Python, Tableau, and Visualization. They’re also known for soft skills such as Creativity, Detail oriented, and Interpersonal skills.
We break down the percentage of Analytical Data Miners that have these skills listed on their resume here:
- Python, 12%
Instructed students in the use of R, Python, SQL, Excel, and Tableau.
- Tableau, 11%
Used Tableau to create patient reports tailored for providers and their medical teams.
- Visualization, 11%
Implemented clinical reporting programs that were utilized by both clinical and data management teams which aided in data visualization and reporting.
- Data Analysis, 9%
Assisted in investment selection by recommending property purchases after reviewing data analysis.
- Power Bi, 7%
Created multiple data visualization solution for initial Power BI business preview.
- BI, 6%
Worked as a data architect delivering BI solutions for the agriculture and bio-tech industry to support predictive analysis and information-based decision-making.
Most analytical data miners use their skills in "python," "tableau," and "visualization" to do their jobs. You can find more detail on essential analytical data miner responsibilities here:
Creativity. The most essential soft skill for an analytical data miner to carry out their responsibilities is creativity. This skill is important for the role because "developers are the creative minds behind new computer software." Additionally, an analytical data miner resume shows how their duties depend on creativity: "involved in setting up the kafka streams framework which is the core of enterprise inventory. "
Detail oriented. Another essential skill to perform analytical data miner duties is detail oriented. Analytical data miners responsibilities require that "developers often work on many parts of an application or system at the same time and must therefore be able to concentrate and pay attention to detail." Analytical data miners also use detail oriented in their role according to a real resume snippet: "developed a java 8 service that provided detailed predicted cost savings on peak demand. "
Interpersonal skills. analytical data miners are also known for interpersonal skills, which are critical to their duties. You can see how this skill relates to analytical data miner responsibilities, because "software developers must be able to work well with others who contribute to designing, developing, and programming successful software." An analytical data miner resume example shows how interpersonal skills is used in the workplace: "provided superior customer service, pleasant interpersonal skills, analytical, and comprehensive problem solving skills. "
Problem-solving skills. analytical data miner responsibilities often require "problem-solving skills." The duties that rely on this skill are shown by the fact that "because developers are in charge of software from beginning to end, they must be able to solve problems that arise throughout the design process." This resume example shows what analytical data miners do with problem-solving skills on a typical day: "reviewed existing gap reporting system written as java m/r job and came up with the solution for boosting the m/r performance. "
Analytical skills. Another common skill required for analytical data miner responsibilities is "analytical skills." This skill comes up in the duties of analytical data miners all the time, as "developers must analyze users’ needs and then design software to meet those needs." An excerpt from a real analytical data miner resume shows how this skill is central to what an analytical data miner does: "developed a mapreduce program in java to classify and analyze data on the shark cluster. "
Communication skills. Lastly, "communication skills" is an important element of what an analytical data miner does. Analytical data miner responsibilities require this skill because "developers must be able to give clear instructions to others working on a project." This resume example highlights how analytical data miner duties rely on this skill: "worked in a data warehousing project which provided business intelligence services to a leading global telecommunication company. "
The three companies that hire the most analytical data miners are:
- Ernst & Young44 analytical data miners jobs
- JPMorgan Chase & Co.8 analytical data miners jobs
- University of Rochester5 analytical data miners jobs
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Compare different analytical data miners
Analytical data miner vs. Business intelligence specialist
A Business Intelligence Specialist is responsible for evaluating strategic techniques and operational processes that would support business functions and achieve goals efficiently. They assess technical applications and develop solutions for complex procedures to minimize downtimes and potential risks. They coordinate with system analysts to generate data and codes and design applications and servers to implement business decisions. A specialist must have excellent critical-thinking and technical skills to manage accounts and ensure clients' timely deliverables.
While similarities exist, there are also some differences between analytical data miners and business intelligence specialist. For instance, analytical data miner responsibilities require skills such as "python," "bi," "cloud," and "powerpoint." Whereas a business intelligence specialist is skilled in "analytics," "business intelligence tools," "architecture," and "data warehousing." This is part of what separates the two careers.
Business intelligence specialists really shine in the finance industry with an average salary of $98,172. Comparatively, analytical data miners tend to make the most money in the health care industry with an average salary of $90,088.On average, business intelligence specialists reach lower levels of education than analytical data miners. Business intelligence specialists are 5.4% less likely to earn a Master's Degree and 2.1% less likely to graduate with a Doctoral Degree.Analytical data miner vs. Business intelligence lead
Business intelligence generally leads to operating data modeling design and survey in the entire organization. Their responsibilities include reviewing and verifying customer data, directing the dissemination of data to the data warehouse, and establishing policies and protocols for the collection and examination of data. Also, they create or locate new data procurement and operating programs as well as collaborate with the IT department to install software and hardware enhancements. Additionally, they observe analytics and metrics results, execute new data analysis programs, examine customer files to make sure cohesion of data collection and usage as well as present data profiling to determine and recognize anomalies.
Each career also uses different skills, according to real analytical data miner resumes. While analytical data miner responsibilities can utilize skills like "python," "tableau," "bi," and "metrics," business intelligence leads use skills like "analytics," "project management," "dashboards," and "client facing."
Business intelligence leads earn a higher average salary than analytical data miners. But business intelligence leads earn the highest pay in the finance industry, with an average salary of $119,983. Additionally, analytical data miners earn the highest salaries in the health care with average pay of $90,088 annually.In general, business intelligence leads achieve similar levels of education than analytical data miners. They're 4.9% less likely to obtain a Master's Degree while being 2.1% less likely to earn a Doctoral Degree.Analytical data miner vs. Business intelligence senior developer
Senior business intelligence developers are in charge of working within the BI team to provide dashboard and reporting solutions that meet the demands of the organization. Their tasks include planning, developing, and sustaining business intelligence solutions. They create and implement queries once data are requested. Also, they give information through graphics and reports as well as upgrade and develop the documentation. Skills required include excellent communication, organizational, and time management skills. Also, candidates must be flexible, adaptable, and accountable to manage numerous distinct priorities.
The required skills of the two careers differ considerably. For example, analytical data miners are more likely to have skills like "python," "tableau," "bi," and "metrics." But a business intelligence senior developer is more likely to have skills like "business intelligence," "analytics," "dashboards," and "ssrs."
Business intelligence senior developers earn the best pay in the manufacturing industry, where they command an average salary of $107,428. Analytical data miners earn the highest pay from the health care industry, with an average salary of $90,088.Most business intelligence senior developers achieve a similar degree level compared to analytical data miners. For example, they're 3.7% less likely to graduate with a Master's Degree, and 1.1% less likely to earn a Doctoral Degree.Analytical data miner vs. Business intelligence architect
A business intelligence architect is in charge of establishing data structures and business intelligence for an organization. Their responsibilities typically include designing systems and tools according to the company's needs, studying the feedback of clients, processing and analyzing extensive data, identifying areas needing improvement, and implementing solutions against problem areas. They must also provide technical support to various departments and employees, enforcing corrective measures as required. Furthermore, as a business intelligence architect, it is essential to lead teams to reach goals, all while implementing the company's data security policies and regulations.
Even though a few skill sets overlap between analytical data miners and business intelligence architects, there are some differences that are important to note. For one, an analytical data miner might have more use for skills like "python," "tableau," "bi," and "metrics." Meanwhile, some responsibilities of business intelligence architects require skills like "analytics," "dashboards," "business intelligence solutions," and "data warehousing. "
The manufacturing industry tends to pay the highest salaries for business intelligence architects, with average annual pay of $111,153. Comparatively, the highest analytical data miner annual salary comes from the health care industry.business intelligence architects reach similar levels of education compared to analytical data miners, in general. The difference is that they're 4.1% more likely to earn a Master's Degree, and 2.3% less likely to graduate with a Doctoral Degree.Types of analytical data miner
Updated January 8, 2025
