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Intern Python Data Science Jobs in Bixby, OK (NOW HIRING)

... data science, biomedical engineering, or a related field (degree must be conferred on or before agreed upon start date) * Experience with quantitative data analysis (Python and/or R) * Experience ...

The intern will assist in building, maintaining, and optimizing Power BI dashboards and reports ... Current junior, senior, or recent graduate in Computer Science, Data Analytics, Statistics ...

Power BI Intern

Tulsa, OK · On-site

$15/hr

The intern will assist in building, maintaining, and optimizing Power BI dashboards and reports ... Current junior, senior, or recent graduate in Computer Science, Data Analytics, Statistics ...

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Intern Python Data Science information

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How much do intern python data science jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for intern python data science in Bixby, OK is $20.71, according to ZipRecruiter salary data. Most workers in this role earn between $15.91 and $22.55 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Intern Python Data Science, and why are they important?

To excel as an Intern Python Data Science, you should have a solid grasp of Python programming, statistics, and foundational data analysis concepts, typically supported by coursework or academic projects in data science or related fields. Familiarity with tools like Jupyter Notebook, Pandas, NumPy, and basic machine learning libraries such as scikit-learn is commonly expected. Curiosity, problem-solving, and the ability to communicate findings clearly are standout soft skills in this role. These competencies enable interns to effectively support data-driven projects, contribute to team goals, and develop practical experience essential for a future data science career.

What types of projects can I expect to work on as an Intern Python Data Science?

As an Intern Python Data Science, you will typically work on projects involving data cleaning, exploratory data analysis, and the development of predictive models using Python libraries like pandas, NumPy, and scikit-learn. You may be tasked with supporting ongoing research, building data visualizations, or automating data collection processes. Collaboration with data scientists and engineers is common, offering opportunities to learn best practices in code review, version control, and teamwork. These experiences provide a solid foundation for more advanced roles in data science.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often focus on the most impactful features or data subsets to optimize model performance and efficiency.

What is the salary of Python intern?

The salary of a Python intern typically ranges from $15 to $25 per hour, depending on the location, company, and level of experience. Interns often receive stipends or hourly wages and may also gain valuable skills in Python programming, data analysis, and tools like Jupyter Notebook or Pandas during their internship.

Is 30 dollars an hour good for an internship?

For an intern in Python Data Science, earning $30 an hour is above average, as many internships pay between $15 and $25 per hour. This rate reflects the specialized skills in programming, data analysis, and tools like Python and Jupyter notebooks, and may indicate a more competitive or advanced internship position.

What does an Intern Python Data Science do?

An Intern Python Data Science assists data science teams with tasks such as data cleaning, analysis, and visualization, primarily using Python programming. They may work on projects involving data collection, processing, and building simple predictive models. Interns are also expected to learn and apply various data science techniques and tools, often under the guidance of experienced data scientists. This role provides hands-on experience and exposure to real-world data challenges, helping interns develop their technical and analytical skills.

What is the difference between Intern Python Data Science vs Intern Data Analyst?

AspectIntern Python Data ScienceIntern Data Analyst
Required SkillsPython, data analysis, machine learning basicsExcel, SQL, data visualization
Work EnvironmentTech companies, startups, research labsBusiness, finance, marketing departments
Common TasksData cleaning, modeling, scriptingData reporting, dashboard creation

Intern Python Data Science roles focus on programming, machine learning, and advanced data analysis, often in tech-driven environments. Intern Data Analyst positions emphasize data reporting, visualization, and basic analysis in business settings. While both roles require analytical skills, Intern Python Data Science roles demand coding proficiency, whereas Intern Data Analyst roles focus more on data presentation and interpretation.

Is 30 too late for data science?

Age is not a barrier to becoming a data science intern; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming in Python, understanding statistics, and working with tools like Jupyter or SQL, regardless of age.
Mathematical Statistician (Data Scientist) - Direct Hire

Mathematical Statistician (Data Scientist) - Direct Hire

US Department of the Treasury

Tulsa, OK • On-site

$74K/yr

Other

Posted 12 days ago


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

238th of 693 rated public administrative organizations


Job description

WHAT IS DATA AND ANALYTICS?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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