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Entry Level Intelligence Analyst Jobs in Oklahoma

Americanfidelity

Data Scientist

Oklahoma City, OK · Hybrid

... analysis, forecasting, machine learning, deep learning, neural networks, artificial intelligence ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

American Fidelity

Data Scientist

Oklahoma City, OK · On-site

... analysis, forecasting, machine learning, deep learning, neural networks, artificial intelligence ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

Pwc

AI & GenAI Data Scientist - Manager

Tulsa, OK

$99K - $232K/yr

... Analytics/Science, Artificial Intelligence and Robotics - At least one of the following ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Posted today

Pwc

AI & GenAI Data Scientist - Manager

Oklahoma City, OK

$99K - $232K/yr

... Analytics/Science, Artificial Intelligence and Robotics - At least one of the following ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Posted today

Investor Economics

Lead Generation Agent

Norman, OK · Hybrid

... ENTRYLEVEL What You Can Expect from Us At ISS STOXX, our people are our driving force. We are ... ISS Market Intelligence (ISS MI) is a leading provider of data, insights, and market engagement ...

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Entry Level Intelligence Analyst information

See Oklahoma salary details

$37.9K

$92.4K

$142.7K

How much do entry level intelligence analyst jobs pay per year?

As of Aug 26, 2026, the average yearly pay for entry level intelligence analyst in Oklahoma is $92,387.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,100.00 and $111,300.00 per year, depending on experience, location, and employer.

What is an entry level intelligence analyst?

Entry level intelligence analysts are professionals who collect, evaluate, and interpret information to support decision-making in areas such as national security, law enforcement, or business. They use various sources, including open-source data, databases, and reports, to identify patterns, threats, or opportunities relevant to their organization. Typically, these roles require strong analytical skills, attention to detail, and the ability to communicate findings clearly. Entry level analysts often work under the supervision of more experienced staff, gaining experience as they contribute to larger intelligence projects.

What does an entry level intelligence analyst do?

An entry-level intelligence analyst works for a government agency, contractor, or law enforcement agency. In this career, your duties include working to gather and perform analysis on information. You assess data to identify threats and recommend a course of action to your superiors. In an entry-level position, your responsibilities may focus on trying to assist senior intelligence analysts by organizing raw data and selecting relevant information. Consulting firms and corporations may hire business intelligence analysts to conduct analysis and research of markets, competitors, and industry innovators.

What are the key skills and qualifications needed to thrive as an entry level intelligence analyst, and why are they important?

To thrive as an Entry Level Intelligence Analyst, you need strong analytical thinking, attention to detail, and a bachelor's degree in fields like criminal justice, international relations, or political science. Familiarity with data analysis tools, intelligence databases, and platforms such as Microsoft Excel or specialized geospatial systems is often required. Effective communication, critical thinking, and discretion are crucial soft skills for collaborating with teams and handling sensitive information. These skills and qualities are vital for accurately interpreting data, supporting decision-making, and maintaining security standards in intelligence work.

What are some common challenges faced by entry level intelligence analysts, and how can they be overcome?

Entry level intelligence analysts often face the challenge of processing large volumes of complex information while meeting tight deadlines. Adapting to specialized analytical tools and learning to distinguish between relevant and irrelevant data can also be demanding. Building strong relationships with colleagues and seeking mentorship can help new analysts develop critical thinking skills and gain confidence. Regularly reviewing best practices and participating in training opportunities can further ease the transition into this fast-paced role.
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Entry Level Intelligence Analyst jobs near you
Infographic showing various Entry Level Intelligence Analyst job openings in Oklahoma as of August 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $92,387 per year, or $44.4 per hour.

Data Analyst III/II/I

Oklahoma City, OK

Americanfidelity
See more jobs at Americanfidelityexternal

Full-time

Re-posted 10 days 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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