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Internship Python R Jobs (NOW HIRING)

Cigna

Actuarial Internship - Summer 2027

Franklin, TN · On-site +1

Our internship is a key pipeline into full-time roles in the AEDP - our primary pathway for ... Python, R, SQL, AIenabled tools, or other emerging technologies to support analysis and drive ...

Cigna

Actuarial Internship - Summer 2027

Austin, TX · On-site +1

Our internship is a key pipeline into full-time roles in the AEDP - our primary pathway for ... Python, R, SQL, AIenabled tools, or other emerging technologies to support analysis and drive ...

Cigna

Actuarial Internship - Summer 2027

Denver, CO · On-site +1

Our internship is a key pipeline into full-time roles in the AEDP - our primary pathway for ... Python, R, SQL, AIenabled tools, or other emerging technologies to support analysis and drive ...

AEI

Fall Intern: Housing Center

Washington, DC

$17 - $22.50/hr

Interns will also gain exposure to the use of AI tools in a research and policy environment. The ... Python, R, Java, or SAS, is preferred but not required. Applicants should be available to ...

AEI

Fall Intern: Housing Center

Washington, DC · On-site

$17 - $22.50/hr

Interns will also gain exposure to the use of AI tools in a research and policy environment. The ... Python, R, Java, or SAS, is preferred but not required. Applicants should be available to ...

AEI

Fall Intern: Housing Center

Washington, DC · On-site

$17 - $22.75/hr

Interns will also gain exposure to the use of AI tools in a research and policy environment. The ... Python, R, Java, or SAS, is preferred but not required. Applicants should be available to ...

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Internship Python R information

What are the key skills and qualifications needed to thrive as an Internship Python R, and why are they important?

To thrive in a Python/R internship, you need foundational knowledge in programming with Python and R, basic statistics, and a relevant academic background in computer science, data science, or a related field. Familiarity with data analysis libraries (like pandas, NumPy, tidyverse), version control systems (such as Git), and data visualization tools is typically required. Strong problem-solving abilities, attention to detail, and the willingness to learn make candidates stand out. These skills are crucial for effectively contributing to data-driven projects and adapting to the learning-focused environment of an internship.

What types of projects or tasks can I expect to work on during a Python/R internship?

As a Python/R intern, you’ll typically assist with data analysis, data cleaning, and visualization projects, often working alongside experienced data scientists or analysts. Many internships involve using Python or R to automate data processing, support research efforts, or build basic machine learning models. You may also contribute to documentation, testing code, and presenting findings to your team. This hands-on experience is designed to strengthen your programming skills and expose you to collaborative workflows common in data-driven environments.

What are Internship Python R positions?

Internship Python R positions are entry-level opportunities for students or recent graduates to gain practical experience working with Python and R programming languages. These internships typically involve tasks such as data analysis, scripting, software development, or research projects that utilize Python and R for statistical computing and data manipulation. Interns learn valuable skills in coding, problem-solving, and collaborating on real-world projects, often in fields like data science, finance, healthcare, or academia. They provide a stepping stone for building a career in technology or data-driven industries.

What is the difference between Internship Python R vs Data Analyst?

AspectInternship Python RData Analyst
Required SkillsBasic Python and R programming, data manipulationData analysis, SQL, visualization tools
Work EnvironmentInternship setting, entry-level projectsFull-time, corporate or research settings
CertificationsOptional, often includes online coursesOften requires or prefers certifications in data analysis or related fields

Internship Python R roles are entry-level positions focusing on learning and assisting with data projects using Python and R. Data Analyst roles are more advanced, involving comprehensive data analysis, reporting, and decision-making. Internships serve as a stepping stone toward full Data Analyst positions, which require more experience and skills.

What cities are hiring for Internship Python R jobs? Cities with the most Internship Python R job openings:
What are the most commonly searched types of Python R jobs? The most popular types of Python R jobs are:
What states have the most Internship Python R jobs? States with the most job openings for Internship Python R jobs include:
Internship Python R jobs near you

Data Analysis Trainer

Technology Pvt. Ltd.

Manhattan, NY • Remote

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Job Description: We are seeking a skilled Data Analysis Trainer to provide high-quality training sessions to individuals and groups. This position is ideal for both experienced professionals and fresh graduates who are passionate about teaching data analysis concepts, tools, and techniques. As a freelance Data Analysis Trainer, you will design, develop, and deliver engaging courses covering fundamental to advanced data analysis skills.

Key Responsibilities: Course Development: Design and create comprehensive training programs in data analysis, tailored for various skill levels, including beginner, intermediate, and advanced learners. Topics include data cleaning, exploratory data analysis, statistical analysis, and data visualization. Content Creation: Develop and regularly update instructional materials such as presentations, coding exercises, datasets, and real-world projects that reflect current industry practices and tools.

Training Delivery: Conduct live, interactive training sessions via online platforms, focusing on essential data analysis skills like data manipulation, statistical techniques, and visualization methods. Student Assessment: Evaluate student performance through quizzes, assignments, and practical projects. Provide constructive feedback to help students improve their data analysis skills and understanding.

Support and Mentorship: Offer personalized support to students, addressing their questions and assisting with troubleshooting issues related to data analysis techniques, tools, and coding. Continuous Improvement: Stay updated with the latest trends and advancements in data analysis, including new tools and methodologies, and incorporate these into the training curriculum. Qualifications: For Experienced Professionals: Experience: Minimum of 2-5 years of professional experience in data analysis, including hands-on experience with data analysis tools, techniques, and methodologies.

Teaching Experience: Previous experience in teaching or training, especially in a freelance or remote capacity, is highly desirable. Technical Skills: Proficiency in data analysis tools and programming languages such as Python, R, SQL, and data visualization tools like Tableau or Power BI. Familiarity with statistical analysis software (e.g., SPSS, SAS) is a plus.

Certifications: Relevant certifications in data analysis or related fields (e.g., Microsoft Certified Data Analyst Associate, Google Data Analytics Professional Certificate) are preferred but not mandatory. Communication Skills: Excellent communication skills with the ability to clearly and effectively explain complex data analysis concepts. For Freshers: Education: A degree or certification in Data Analysis, Statistics, Computer Science, Mathematics, or a related field.

Technical Skills: Basic knowledge of data analysis tools and techniques, gained through academic coursework, internships, or personal projects. Familiarity with Python, R, or SQL, and data visualization tools is a plus. Passion for Teaching: A strong interest in teaching and mentoring students in data analysis, with a commitment to developing effective training methods.

Communication Skills: Strong verbal and written communication skills, capable of making complex data analysis topics accessible to diverse audiences. #J-18808-Ljbffr

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