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Entry Level Baseball Data Analyst Jobs in Oklahoma

Pwc

AI & GenAI Data Scientist - Manager

Tulsa, OK

$99K - $232K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

American Fidelity

Data Scientist

Oklahoma City, OK · On-site

Engineer analysis pipelines iteratively to provide insights at scale. Develop comprehensive ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

Americanfidelity

Data Scientist

Oklahoma City, OK · Hybrid

Engineer analysis pipelines iteratively to provide insights at scale. Develop comprehensive ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

Moore Public Schools

Information Analyst

Moore, OK · On-site

$16.25/hr

... data entry; Level B duties may include but not be limited to complete knowledge of student ... Description 11.21 - Information Analyst A, B, C Application Procedure Posting closes at 4:00 p.m ...

BOK Financial

Document Imaging Analyst I

Tulsa, OK · On-site

They excel in system integration, secure data handling, and fostering a collaborative workplace. By ... This entry-level Document Imaging Analyst I role focuses on accurately scanning and indexing up to ...

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Entry Level Baseball Data Analyst information

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How much do entry level baseball data analyst jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for entry level baseball data analyst in Oklahoma is $30.40, according to ZipRecruiter salary data. Most workers in this role earn between $19.52 and $33.94 per hour, depending on experience, location, and employer.

What is an entry level baseball data analyst?

An Entry Level Baseball Data Analyst is responsible for collecting, analyzing, and interpreting baseball-related data to support decision-making in player evaluation, game strategy, and team performance. They use statistical models, databases, and programming languages like SQL, Python, or R to generate insights. This role often involves working with coaches, scouts, and front-office staff to apply data-driven recommendations. Strong analytical skills, attention to detail, and knowledge of baseball metrics are essential for success in this position.

What are some typical projects or tasks an entry level baseball data analyst might work on during a season?

As an Entry Level Baseball Data Analyst, you'll regularly collect and organize player performance data, prepare reports for coaches or scouts, and maintain large databases of game statistics. You may assist in analyzing trends such as player tendencies, pitch effectiveness, or opponent strategies to support game preparation and evaluate potential trades or draft picks. Collaboration with other analysts, coaches, and front office staff is common, so you'll often attend meetings to present findings and make recommendations. This role provides hands-on experience with real-time analytics and offers opportunities to contribute insights that can impact team decisions and player development.

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

To thrive as an Entry Level Baseball Data Analyst, you need strong analytical skills, a solid understanding of baseball statistics, and a relevant degree such as mathematics, statistics, or a related field. Familiarity with data analysis tools like SQL, R, Python, and databases, as well as experience with sports analytics platforms, is highly beneficial. Clear communication, teamwork, and attention to detail are important soft skills for translating data insights and working with coaches or scouting staff. These abilities are essential to effectively interpret data, support team decision-making, and help drive competitive strategies in a fast-paced sports environment.

What are the most commonly searched types of Baseball Data Analyst jobs in Oklahoma?

The most popular types of Baseball Data Analyst jobs in Oklahoma are:

What are popular job titles related to Entry Level Baseball Data Analyst jobs in Oklahoma?

For Entry Level Baseball Data Analyst jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Entry Level Baseball Data Analyst jobs in Oklahoma look for?

The top searched job categories for Entry Level Baseball Data Analyst jobs in Oklahoma are:

What cities in Oklahoma are hiring for Entry Level Baseball Data Analyst jobs?

Cities in Oklahoma with the most Entry Level Baseball Data Analyst job openings:

Entry Level Baseball Data Analyst jobs near you
Infographic showing various Entry Level Baseball Data Analyst job openings in Oklahoma as of July 2026, with employment types broken down into 82% Full Time, 9% Part Time, and 9% Contract. Highlights an 96% In-person, and 4% Remote job distribution, with an average salary of $63,237 per year, or $30.4 per hour.

Data Analyst III/II/I

Oklahoma City, OK

Americanfidelity
See more jobs at Americanfidelityexternal

Full-time

Re-posted 14 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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