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Entry Level Data Mining Jobs (NOW HIRING)

Kiewit

Mining Engineer - Kiewit Mining Group 2026

Gillette, WY · On-site

$86K - $95K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Requisition ID: 180303 Job Level: Entry Level Home District/Group: Kiewit Mining District ... Review and analyze data relative to the project, complete plans and specification reviews for ...

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How much do entry level data mining jobs pay per year?

As of Aug 16, 2026, the average yearly pay for entry level data mining in the United States is $69,999.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,000.00 and $85,000.00 per year, depending on experience, location, and employer.

What is an entry level data mining?

An Entry Level Data Mining job involves collecting, cleaning, and analyzing large datasets to identify patterns and trends. Professionals in this role use statistical techniques, programming languages like Python or SQL, and data visualization tools to extract meaningful insights. They often support business decisions by preparing reports, building predictive models, and ensuring data quality. This role is ideal for individuals with a background in data science, computer science, or related fields who want to gain hands-on experience in handling and interpreting data.

What does an entry level data mining do?

A typical day for an Entry Level Data Mining professional often involves cleaning and organizing raw data, running exploratory analyses, and assisting in building models or algorithms under the guidance of senior team members. Collaboration with data analysts, engineers, and business teams is common, as you may be responsible for preparing reports or visualizations that help inform decision-making. You may also spend time learning new data mining techniques or tools to enhance your efficiency and broaden your skill set. The role offers a mix of technical tasks and teamwork, making it a great opportunity for those eager to grow within the field of data science.

What are the key skills and qualifications needed to thrive in entry level data mining, and why are they important?

To thrive as an Entry Level Data Mining professional, a solid understanding of statistics, basic programming (such as Python or R), and data analysis is typically required, often backed by a degree in computer science, mathematics, or a related field. Familiarity with data mining tools like Weka, RapidMiner, or SQL databases is beneficial, and certifications in analytics or data science can enhance your prospects. Strong attention to detail, analytical thinking, and effective communication are important soft skills for collaborating and conveying findings to non-technical stakeholders. These competencies ensure accurate data extraction, meaningful insights, and successful teamwork essential for effective contributions in data-driven environments.

How to get started in entry level data mining?

To start an entry-level data mining role, develop foundational skills in data analysis, statistics, and programming languages like Python or R. Gain experience with data manipulation tools such as SQL and familiarize yourself with data visualization software; obtaining certifications like Microsoft Data Analyst or Google Data Analytics can also improve your prospects.
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Entry Level Data Mining jobs near you
Infographic showing various Entry Level Data Mining job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $69,999 per year, or $33.7 per hour.

Data Analyst III/II/I

Americanfidelity

Oklahoma City, OK • On-site

Full-time

Re-posted 2 hours ago

Job description

* Plan, implement and execute data mining and predictive modeling related projects to which they are assigned to deliver intended business value propositions, on time and within scope according to agreed upon priorities. The Data Analyst is accountable for working collaboratively with Data Navigators and for the successful delivery of all projects under their supervision.

* Assist the Research & Development team, Executive Management, and AFA through the production and maintenance of data and metrics regarding demographics, market trends, behavioral economics, and socioeconomic shifts.

* Drive business value through actionable insight and opportunity identification as facilitated through comprehensive exploratory, interactive, adaptive, and iterative data mining, machine learning, data science, clustering, artificial intelligence (AI), and predictive modeling related analysis which have generally high complexity and/or business risk.

Skills of Ideal Candidate:

1. Advanced knowledge of one or more differing statistical programming languages such as SAS, R or Stata.

2. Ability to develop structure and/or program databases specifically within an MS SQL environment, skilled in the utilization of Structured Query Language (SQL) for interacting with data sets. Understanding of data structures and ability to become proficient in mining data structures and lineage in support of data foot printing and inventory techniques.

3. Skilled in Robotic Process Automation tools such as UI Path and Artificial Intelligence tools like Data Robot

4. Skilled in MS Office Suite including MS Access, Excel, PowerPoint, Word and MS SharePoint.

5. Familiarity with the following disciplines

Natural Language Processing: Interaction between computers and humans

Machine Learning: using computers to improve as well as develop algorithms

Conceptual modeling: to be able to share and articulate conceptual approaches to solving business questions/problems

Statistical analysis and Predictive modeling

Hypothesis testing: design hypothesis, document control and test with appropriate modeling and experimentation

6. Ability to query databases and datasets and perform statistical analysis on enterprise-class database systems.

7. Exceptional presentation skills.

8. Being able to work in a fast-paced multidisciplinary environment as in a competitive landscape new data keeps flowing in rapidly and the world is constantly changing.

9. Strong negotiation skills.

10.Strong communication skills, including written, verbal and listening which can be deployed successfully when addressing entry level Colleagues to management to senior executives. This includes the ability to speak confidently in both business and technological surroundings and appropriately transliterate between the two.

11. Exceptional analytical thinking and problem solving skills.

12. Exceptional understanding of business and business strategy.

13.Strongplanning skills.

14. Exceptional organizational skill and ability to work autonomously.

15. Experience using data visualization tools such as QlikSense or Tableau

16. Innovative curiosity

17.Strongknowledge of Data Science

18.Ability to deal with ambiguity

Education Requirements:

Data Analyst III: Actuarial Designationscan substitute for PhD.AFA specific data experience will be considered in lieu of PhD oncase by casebasis

Data Analyst I/II: High school diploma or equivalent

#AFC

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