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Entry Level Data Visualization Jobs in Oklahoma (NOW HIRING)

... visualization - Implementing data security best practices to protect sensitive information and ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... visualization - Implementing data security best practices to protect sensitive information and ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Entry Level Data Visualization information

See Oklahoma salary details

$9

$17

$24

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

As of Jul 16, 2026, the average hourly pay for entry level data visualization 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 Visualization job?

An Entry Level Data Visualization job involves creating charts, graphs, and dashboards to help analyze and communicate data effectively. Professionals in this role use tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn) to present data in a clear and visually appealing way. They often work with data analysts and business teams to transform raw data into insights that drive decision-making. Strong analytical skills, attention to detail, and basic programming or SQL knowledge can be helpful in this role.

What are the key skills and qualifications needed to thrive in the Entry Level Data Visualization position, and why are they important?

To thrive as an Entry Level Data Visualization professional, you need a solid understanding of data analysis, basic statistical concepts, and visual storytelling, typically supported by a bachelor’s degree in a related field. Familiarity with tools such as Tableau, Power BI, or Excel, and basic programming knowledge in Python or R, are commonly expected and may be enhanced by certifications in data analytics or visualization. Strong communication, attention to detail, and a collaborative attitude help you explain complex data insights to diverse audiences and work effectively within cross-functional teams. These skills and qualities are essential for translating data into actionable insights and creating impactful visuals that inform business decision-making.

What are the typical day-to-day responsibilities of someone in an Entry Level Data Visualization role?

Entry Level Data Visualization professionals usually spend their days gathering data from various sources, cleaning or preparing it for analysis, and building charts, graphs, or dashboards to present findings. You’ll often collaborate with analysts, project managers, or business teams to understand project requirements and iterate on visual solutions based on feedback. Reviewing data accuracy, updating reports, and attending team meetings to discuss progress or new projects are also common. This role offers a great opportunity to sharpen both technical and communication skills while playing a key part in how your organization makes data-driven decisions.

Full-time

Posted 28 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

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