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Entry Level Machine Learning Jobs in Yukon, OK (NOW HIRING)

Americanfidelity

Data Scientist

Oklahoma City, OK · Hybrid

Research and engineer analysis, forecasting, machine learning, deep learning, neural networks ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

American Fidelity

Data Scientist

Oklahoma City, OK · On-site

Research and engineer analysis, forecasting, machine learning, deep learning, neural networks ... entry level Colleagues to management to senior executives. This includes the ability to speak ...

Pwc

AI & GenAI Data Scientist - Manager

Oklahoma City, OK · On-site

$99K - $232K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

All JobsMachine Learning JobsEntry Level Machine Learning JobsEntry Level Machine Learning Jobs in Yukon, OK

Entry Level Machine Learning information

See Yukon, OK salary details

$10

$14

$18

How much do entry level machine learning jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for entry level machine learning in Yukon, OK is $14.73, according to ZipRecruiter salary data. Most workers in this role earn between $13.17 and $16.01 per hour, depending on experience, location, and employer.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio. Internships, certifications, and participating in competitions like Kaggle can also improve your chances of entering the field without prior experience.
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Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in Yukon, OK as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $30,645 per year, or $14.7 per hour.

Data Scientist

Oklahoma City, OK • Hybrid

Americanfidelity
See more jobs at Americanfidelityexternal

Full-time

Posted 26 days ago

Job description

Job Description:

Work with large, complex data sets using to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed to complete end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.

Engineer analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of data structures and metrics, advocating for changes where needed in systems, products and processes.

Research and engineer analysis, forecasting, machine learning, deep learning, neural networks, artificial intelligence and optimization methods to improve the quality of products; example application areas include customer segmentation modeling and end-user behavioral modeling/prediction.

Technical Skills and Requirements:

  • Expert in multiple statistical software (e.g., R, Python, Julia, MATLAB, pandas) and associated data science libraries (scikit-learn).
  • Expert in database languages (e.g., SQL).
  • Experience creating meaningful data visualizations and/or interactive dashboards that communicate findings and business impacts using platforms such as Tableau, Qlik, Power BI, RShiny, plotly, and d3.js.
  • Applied experience with machine learning on large datasets using Big Data tools such as Apache's Hadoop or Spark
  • Expert in deep learning techniques and neural networks using languages such as as TensorFlow
  • Expert in multiple major programming language (C/C++. C#, Java, Python, etc.) or optimization modeling languages (AMPL, GAMS, AIMMS, OPL, etc.)
  • Experience with data science methods related to data architecture, data cleaning, data and feature engineering, and predictive analytics.
  • Strong background in modeling large scale discrete, nonlinear or stochastic mathematical optimization models and engineering efficient optimization algorithms.
  • Familiarity with natural language processing, machine learning, statistical modeling, predictive modeling, and hypothesis testing.
  • Familiarity working with both structured and unstructured data, including textual data.
  • Ability to work in a fast-paced environment.
  • Exceptionally 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.
  • Exceptional analytical thinking and problem solving skills.
  • Exceptional understanding of business and business strategy.
  • Exceptional planning skills.
  • Exceptional organizational skill and ability to work autonomously.

Education:

Master's degree in related field required.

Location:

This is a hybrid position. Applicants must be located in OKC Metro area or willing to relocate.

#AFC

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