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Entry Level Artificial Intelligence Jobs in Oklahoma

Pwc

AI & GenAI Data Scientist - Manager

Oklahoma City, OK · On-site

$99K - $232K/yr

... Artificial Intelligence and Machine Learning-based solutions at scale. Your work will involve ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Pwc

AI & GenAI Data Scientist - Manager

Tulsa, OK · On-site

$99K - $232K/yr

... Artificial Intelligence and Machine Learning-based solutions at scale. Your work will involve ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Americanfidelity

Data Scientist

Oklahoma City, OK · Hybrid

... artificial intelligence and optimization methods to improve the quality of products; example ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

American Fidelity

Data Scientist

Oklahoma City, OK · On-site

... artificial intelligence and optimization methods to improve the quality of products; example ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

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All JobsArtificial Intelligence JobsEntry Level Artificial Intelligence JobsEntry Level Artificial Intelligence Jobs in Oklahoma

Entry Level Artificial Intelligence information

See Oklahoma salary details

$19.3K

$76.3K

$172.2K

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

As of Sep 7, 2026, the average yearly pay for entry level artificial intelligence in Oklahoma is $76,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,985.00 and $119,757.00 per year, depending on experience, location, and employer.

What are the qualifications to get an entry level artificial intelligence job?

The qualifications necessary for an entry-level artificial intelligence job depend on the exact job that you choose to pursue. You typically need a bachelor’s degree to start in this field. Common degree paths involve various types of math, physics, robotics, cognitive science therapy, graphical modeling, engineering, Bayesian networking, and computer programming languages, science, and coding. Several skills are also helpful, such as being able to work well with others, strong communication skills, the ability to translate highly technical information, and excellent problem-solving abilities.

What are the key skills and qualifications needed to thrive as an entry level artificial intelligence professional?

To thrive as an Entry Level Artificial Intelligence professional, you need a solid understanding of programming languages (such as Python), basic statistics, and machine learning concepts, often supported by a degree in computer science, data science, or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience using data processing libraries are typically required. Analytical thinking, problem-solving abilities, and effective communication help you collaborate with teams and interpret data-driven results. These skills are crucial for building reliable AI solutions and contributing effectively to rapidly evolving projects.

What are some common challenges entry level artificial intelligence professionals face when starting their career, and how can they overcome them?

Entry-level professionals in artificial intelligence often encounter challenges such as bridging the gap between theoretical knowledge and real-world application, keeping up with the fast pace of technological advancements, and collaborating effectively within multidisciplinary teams. To overcome these hurdles, it's helpful to seek mentorship, participate in open-source projects, and continuously update your skills through online courses and workshops. Building strong communication skills will also help when working with colleagues from different backgrounds, such as data engineers, software developers, and business stakeholders.

What is the difference between Entry Level Artificial Intelligence vs Entry Level Data Scientist?

AspectEntry Level Artificial IntelligenceEntry Level Data Scientist
Required CredentialsBachelor's in CS, AI, or related field; basic programming skillsBachelor's in CS, Statistics, or related; knowledge of data analysis
Work EnvironmentTech companies, research labs, startupsBusiness, finance, healthcare, tech firms
Industry UsageDeveloping AI models, machine learning algorithmsAnalyzing data, building predictive models
Common Search IntentEntry level AI roles, AI job requirementsEntry level data science roles, data analysis jobs

Entry Level Artificial Intelligence roles focus on developing AI models and algorithms, often requiring programming and machine learning knowledge. Entry Level Data Scientist positions involve analyzing data and creating predictive models, with overlapping skills but different focus areas. Both roles are common in tech-driven industries and require similar educational backgrounds, but they serve distinct functions within organizations.

How do I start an entry level artificial intelligence career with no experience?

To start an entry-level artificial intelligence career with no experience, focus on building foundational skills in programming languages like Python, learn key concepts such as machine learning and data analysis, and complete online courses or certifications in AI. Gaining practical experience through projects, internships, or contributing to open-source AI initiatives can also improve your prospects.

Which job to go for a beginner in artificial intelligence?

Entry-level artificial intelligence roles typically include positions such as AI intern, junior data analyst, or machine learning assistant. These jobs often require foundational skills in programming (Python or R), basic understanding of algorithms, and familiarity with tools like TensorFlow or scikit-learn, along with a relevant degree or certification. Starting in these roles provides practical experience and a pathway to more advanced AI positions.
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What are the most commonly searched types of Artificial Intelligence jobs in Oklahoma?

The most popular types of Artificial Intelligence jobs in Oklahoma are:

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For Entry Level Artificial Intelligence jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Entry Level Artificial Intelligence jobs in Oklahoma look for?

The top searched job categories for Entry Level Artificial Intelligence jobs in Oklahoma are:

What cities in Oklahoma are hiring for Entry Level Artificial Intelligence jobs?

Cities in Oklahoma with the most Entry Level Artificial Intelligence job openings:

Entry Level Artificial Intelligence jobs near you
Infographic showing various Entry Level Artificial Intelligence job openings in Oklahoma as of August 2026, with employment types broken down into 84% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $76,282 per year, or $36.7 per hour.

Data Analyst III/II/I

Americanfidelity

Oklahoma City, OK • On-site

Full-time

Re-posted 22 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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