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Internship Python Data Science Jobs in Jamestown, NY

Our Science & Technology organization is harnessing the power of technology to make healthcare more ... Python, C++) * Experience with high-dimensional imaging data and waveform/time-series data.

Summary The AI Scientist will work in teams addressing statistical, machine learning and data ... Strong programming skills in Python and C++. * Experience developing scalable, maintainable ...

Snowflake Administrator Senior

North East, PA · On-site +1

$46 - $63.25/hr

Partner with data engineers, architects, and analysts to integrate Snowflake with data systems and ... Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or ...

Graduate degree in Computer Science or a related field, with two or more years of industry ... Python, Java, C/C++). * Experience working with largescale data and production platforms (e.g.

Graduate degree in Computer Science or a related field, with two or more years of industry ... Python, Java, C/C++). * Experience working with largescale data and production platforms (e.g.

Internship Python Data Science information

See Jamestown, NY salary details

$11

$20

$39

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

As of Aug 29, 2026, the average hourly pay for internship python data science in Jamestown, NY is $20.95, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $22.84 per hour, depending on experience, location, and employer.

What is an internship Python data science?

An Internship Python Data Science position is an entry-level role designed for students or recent graduates to gain practical experience in data science using Python. Interns typically work under the supervision of experienced data scientists, assisting with data analysis, cleaning, visualization, and sometimes building machine learning models. They may also collaborate on real-world projects, learning to use tools and libraries like pandas, NumPy, scikit-learn, and Jupyter Notebook. This internship helps individuals develop technical and analytical skills while building a foundation for a career in data science.

What types of projects can I expect to work on during a Python data science internship?

As a Python Data Science intern, you will often work on projects involving data cleaning, exploratory data analysis, model building, and visualization using Python libraries like pandas, NumPy, and scikit-learn. You may assist in preparing datasets, automating data pipelines, or supporting senior data scientists with real-world business problems such as customer analytics or predictive modeling. Collaboration with both technical and non-technical teams is common, providing valuable exposure to the end-to-end data science workflow and opportunities to present your findings.

What are the key skills and qualifications needed to thrive as an internship Python data science?

To thrive as an Internship Python Data Science, you need a solid understanding of statistics, data analysis, and programming in Python, often supported by coursework or academic projects in data science or related fields. Familiarity with tools and libraries such as Pandas, NumPy, Scikit-learn, and Jupyter Notebooks is typically expected. Strong problem-solving abilities, eagerness to learn, and effective communication are valuable soft skills for standing out in this role. These skills ensure interns can analyze data, contribute to team projects, and grow quickly in a fast-evolving technical environment.

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

AspectInternship Python Data ScienceData Analyst Intern
Required SkillsPython, SQL, statistics, machine learning basicsExcel, SQL, data visualization tools
Work EnvironmentTech companies, startups, research labsBusiness, finance, marketing sectors
Typical TasksData cleaning, modeling, predictive analysisData reporting, dashboard creation, trend analysis

Internship Python Data Science and Data Analyst Intern roles share common skills like SQL and data handling but differ mainly in focus. Data Science internships emphasize programming, modeling, and machine learning, while Data Analyst internships focus on data visualization and reporting. Both are valuable entry points in data careers, often found in similar industries and work environments.

What job categories do people searching Internship Python Data Science jobs in Jamestown, NY look for?

The top searched job categories for Internship Python Data Science jobs in Jamestown, NY are:

What cities near Jamestown, NY are hiring for Internship Python Data Science jobs?

Cities near Jamestown, NY with the most Internship Python Data Science job openings:

$125K/yr

Full-time

Posted 4 days ago


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Company rating: 7.5 out of 10

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Job description

WHAT IS LARGE BUSINESS AND INTERNATIONAL?

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 following area(s):
    • LBI - ADCCI - Compliance Planning & Analytics (CP&A), Workload Development & Delivery (WDD). Team will be determined at time of selection.

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 closing date of this announcement.
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:

  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.


AND
You must also meet the following requirement(s):

  • TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens"
  • TIME IN GRADE (TIG): For positions above the GS-05,applicants must meet applicable time-in-grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03 or 04 positions.


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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