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Entry Level Data Science Jobs in Oklahoma (NOW HIRING)

ARL Bio Pharma

Data Processing Chemist

Oklahoma City, OK

$23 - $26/hr

... science and customer service. This is an entry-level role, the Data Processing Chemist I, will be responsible for collaborating with chemists, of various levels, performing supportive tasks to ensure ...

ARL

Data Processing Chemist

Oklahoma City, OK · On-site

$23 - $26/hr

... science and customer service. This is an entry-level role, the Data Processing Chemist I, will be responsible for collaborating with chemists, of various levels, performing supportive tasks to ensure ...

Pwc

US Tech - FTO Senior Associate

Tulsa, OK

$55K - $187K/yr

Analytics/Data Science, Artificial Intelligence/Robotics, Business Administration/Management ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

New

Pwc

Data Engineer - Senior Associate

Oklahoma City, OK · On-site

$77K - $202K/yr

Management Information Systems, Computer and Information Science, Systems Engineering, Electrical ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Pwc

Data Engineer - Senior Associate

Tulsa, OK

$77K - $202K/yr

Management Information Systems, Computer and Information Science, Systems Engineering, Electrical ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Data Science information

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How much do entry level data science jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for entry level data science in Oklahoma is $17.59, according to ZipRecruiter salary data. Most workers in this role earn between $14.86 and $19.76 per hour, depending on experience, location, and employer.

What is an entry level data scientist?

Entry level data science jobs are positions designed for individuals who are starting their careers in the field of data science, often requiring minimal professional experience. These roles typically involve working with data collection, cleaning, and analysis, as well as assisting more senior data scientists with projects. Entry level data scientists are expected to have a foundational understanding of statistics, programming (often in Python or R), and basic machine learning concepts. They may work in various industries, helping organizations gain insights from data to support decision-making.

What types of projects or tasks can I expect to work on as an entry level data scientist?

As an entry-level data scientist, you'll typically work on tasks such as data cleaning, exploratory data analysis, and supporting the development of predictive models. You may also assist in preparing datasets, generating reports, and visualizing data for stakeholders. Collaboration with more senior data scientists and cross-functional teams like engineering or business analysts is common, giving you opportunities to learn and grow your technical and communication skills. These foundational projects are essential for building your expertise and preparing for more complex responsibilities as you advance in your career.

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

To thrive as an Entry Level Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree such as computer science, mathematics, or statistics. Familiarity with technical tools like SQL databases, data visualization software (e.g., Tableau), and machine learning libraries (such as scikit-learn or TensorFlow) is commonly expected. Curiosity, problem-solving ability, and effective communication help you interpret data insights and collaborate with diverse teams. These skills ensure you can extract meaningful insights from data, contribute to data-driven decision-making, and grow within the analytics field.

What is the difference between Entry Level Data Science vs Data Analyst?

AspectEntry Level Data ScienceData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some certificationsBachelor's in Business, Statistics, or related field; certifications optional
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Employer & Industry UsageData-driven roles in tech and researchBusiness insights, reporting, and visualization
Common Search & ComparisonYesYes

Entry Level Data Science and Data Analyst roles often share similar educational backgrounds and work environments. However, data scientists typically focus on building models and advanced analytics, while data analysts concentrate on interpreting data and creating reports. Both roles are essential in data-driven organizations, but they differ in technical complexity and scope.

What are the most commonly searched types of Data Science jobs in Oklahoma? The most popular types of Data Science jobs in Oklahoma are:
What are popular job titles related to Entry Level Data Science jobs in Oklahoma? For Entry Level Data Science jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Science jobs in Oklahoma look for? The top searched job categories for Entry Level Data Science jobs in Oklahoma are:
What cities in Oklahoma are hiring for Entry Level Data Science jobs? Cities in Oklahoma with the most Entry Level Data Science job openings:
Entry Level Data Science jobs near you
Infographic showing various Entry Level Data Science job openings in Oklahoma as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $36,591 per year, or $17.6 per hour.

Data Analyst III/II/I

Americanfidelity

Oklahoma City, OK

Full-time

Re-posted 20 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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