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Entry Level Data Analyst Jobs in Guthrie, OK (NOW HIRING)

Pwc

Data Engineer - Senior Associate

Oklahoma City, OK · On-site

$77K - $202K/yr

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

Nextiny

Entry Level Digital Marketer

Edmond, OK · On-site

We are looking for an entry-level Digital Marketer to join our team. No prior marketing experience ... Analyze campaign performance and provide data-driven insights to improve marketing efforts.

Nextiny

Entry Level Digital Marketer

Edmond, OK

We are looking for an entry-level Digital Marketer to join our team. No prior marketing experience ... Analyze campaign performance and provide data-driven insights to improve marketing efforts.

Intermountain Health

HCC Coding Analyst 1

Oklahoma City, OK · On-site

$28.06 - $44.20/hr

This Position is an entry-level role in Risk Adjustment and will learn to demonstrate general ... Complies with HIPAA law to maintain data privacy and security. * Completes all continuing education ...

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Entry Level Data Analyst information

See Guthrie, OK salary details

$10

$25

$47

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

As of Aug 7, 2026, the average hourly pay for entry level data analyst in Guthrie, OK is $25.06, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $27.98 per hour, depending on experience, location, and employer.

What does an entry level data analyst do?

An Entry Level Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed decisions. They often work with spreadsheets, databases, and data visualization tools to identify trends and generate reports. Typical tasks include cleaning data, creating charts or dashboards, and supporting senior analysts or business teams with actionable insights. This role is ideal for individuals with strong analytical skills and a keen attention to detail, even if they have limited professional experience.

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

AspectEntry Level Data AnalystData Scientist
Required CredentialsBachelor's degree in data-related field; basic knowledge of SQL, Excel, and data visualization toolsBachelor's or master's degree in data science, statistics, or related field; stronger programming and statistical skills
Work EnvironmentEntry-level roles in business, finance, marketing, or healthcare sectors; focus on data reporting and visualizationMore advanced roles often in tech, research, or large organizations; focus on predictive modeling and complex analysis
Employer & Industry UsageCommon in various industries for routine data analysis tasksUsed in industries requiring advanced analytics, machine learning, and predictive insights

While Entry Level Data Analysts focus on basic data collection, cleaning, and reporting, Data Scientists handle complex modeling, machine learning, and predictive analytics. The roles differ mainly in skill level, complexity, and scope of work, but both require a strong foundation in data handling and analysis.

What are some common challenges entry level data analysts face when transitioning from academic projects to real-world business environments?

Entry level data analysts often find that real-world datasets are messier and less structured than those in academic settings, requiring more time spent on data cleaning and preparation. Additionally, business environments may prioritize actionable insights over purely statistical rigor, so learning to communicate findings to non-technical stakeholders is crucial. Collaborating within cross-functional teams and managing multiple deadlines can also be a new challenge, but these experiences help analysts develop strong problem-solving and communication skills that are valuable for career growth.

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

To thrive as an Entry Level Data Analyst, you need strong analytical thinking, basic statistical knowledge, and proficiency in data management, typically supported by a bachelor’s degree in a quantitative field. Familiarity with tools such as Microsoft Excel, SQL, and data visualization platforms like Tableau or Power BI is commonly required. Attention to detail, effective communication, and a willingness to learn help set candidates apart in this role. These skills are vital for accurately interpreting data, generating actionable insights, and clearly conveying findings to support business decisions.
More about Entry Level Data Analyst jobs
What are the most commonly searched types of Data Analyst jobs in Guthrie, OK? The most popular types of Data Analyst jobs in Guthrie, OK are:
What cities near Guthrie, OK are hiring for Entry Level Data Analyst jobs? Cities near Guthrie, OK with the most Entry Level Data Analyst job openings:
Entry Level Data Analyst jobs near you
Infographic showing various Entry Level Data Analyst job openings in Guthrie, OK as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $52,135 per year, or $25.1 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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