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Data Analytics Jobs in Shawnee, OK (NOW HIRING)

Moore Public Schools

Data Processing Analyst

Moore, OK · On-site

... Data Processing Analyst - Technology for the 2026-2027 school year 2.17 Application Procedure This position closes at 4:00 p.m., Tuesday, August 11, 2026 , but will remain open until the position is ...

MidFirst Bank

Data Steward Manager

Oklahoma City, OK · On-site

Responsibilities : • Lead, mentor, and develop a centrally federated team of Data Stewards assigned to specific business data domains. • Supervise a team of Data Quality Analysts responsible for ...

Teleflora

Data Scientist, Modeler

Oklahoma City, OK · On-site +1

A key aspect of this role is the ability to translate complex analyses into clear, compelling narratives for non-technical stakeholders, including senior leadership. The Data Scientist will also ...

Pwc

Data Strategy & Governance -Director

Oklahoma City, OK · On-site

$155K - $410K/yr

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data ...

Acrisure

Manager, Customer Analytics

Oklahoma City, OK · On-site

$1 - $2/hr

What You'll Do We are seeking a Manager of Data Analytics to enhance our customer insights function within a fast-growing SaaS payroll company. This role will be responsible for transforming data ...

Acrisure

Manager, Customer Analytics

Oklahoma City, OK · On-site

$1 - $2/hr

What You'll Do We are seeking a Manager of Data Analytics to enhance our customer insights function within a fast-growing SaaS payroll company. This role will be responsible for transforming data ...

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All JobsData Analytics JobsData Analytics Jobs in Shawnee, OK

Data Analytics information

See Shawnee, OK salary details

$21

$48

$83

How much do data analytics jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for data analytics in Shawnee, OK is $48.36, according to ZipRecruiter salary data. Most workers in this role earn between $38.85 and $54.76 per hour, depending on experience, location, and employer.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What are the key skills and qualifications needed to thrive as a data analytics professional, and why are they important?

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data scientist, data engineer, or reporting specialist. They analyze data to help organizations make informed decisions, often using tools like Excel, SQL, and visualization software, and may require knowledge of statistical methods and programming languages like Python or R.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, often requiring proficiency in tools like Excel, SQL, and Python, and may require relevant certifications or a strong understanding of statistical methods.

What are the most commonly searched types of Data Analytics jobs in Shawnee, OK?

The most popular types of Data Analytics jobs in Shawnee, OK are:

What cities near Shawnee, OK are hiring for Data Analytics jobs?

Cities near Shawnee, OK with the most Data Analytics job openings:

Data Analytics jobs near you
Infographic showing various Data Analytics job openings in Shawnee, OK as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $100,584 per year, or $48.4 per hour.

Data Analyst III/II/I

Oklahoma City, OK • On-site

American Fidelity
Insurance Services • 1 - 5K employees
Learn more about American Fidelityexternal

Full-time

Re-posted 8 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. Strong planning 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. Strong knowledge of Data Science
18. Ability to deal with ambiguity
Education Requirements:
Data Analyst III: Actuarial Designations can substitute for PhD. AFA specific data experience will be considered in lieu of PhD on case by case basis
Data Analyst I/II: High school diploma or equivalent
#AFC

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