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Data Science Teaching Assistant Jobs in Pennsylvania

The Pennsylvania State University

$13.75 - $17.50/hr

AND POSITION REQUIREMENTS The Department ofMathematics, in the Eberly College of Science, has a vacancy available for an undergraduate Teaching Assistant to act as a peer assistant for Math Lab (MATH ...

Penn State University

Teaching Assistant

University Park, PA · On-site

$13.75 - $17.25/hr

AND POSITION REQUIREMENTS The Department of Mathematics, in the Eberly College of Science, has a vacancy available for an undergraduate Teaching Assistant to act as a peer assistant for Math Lab ...

The Pennsylvania State University

$13.75 - $17.50/hr

AND POSITION REQUIREMENTS The Eberly College of Science, Department of Biology, is looking to hire Teaching Assistants to provide support to Biology courses overseen by the teaching faculty during ...

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The Pennsylvania State University

$13.75 - $17.50/hr

AND POSITION REQUIREMENTS The Eberly College of Science, Department of Biology, is looking to hire Teaching Assistants to provide support to Biology courses overseen by the teaching faculty during ...

The Pennsylvania State University

$10.50/hr

AND POSITION REQUIREMENTS The Department of Plant Science is seeking a candidate to serve as a teaching assistant for approximately 6 to 10 hours of work per week during the fall 2026 semester for ...

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All JobsData Science Teaching JobsData Science Teaching Assistant JobsData Science Teaching Assistant Jobs in Pennsylvania

Data Science Teaching Assistant information

What is a data science teaching assistant?

Data Science Teaching Assistants (TAs) support instructors and students in data science courses or bootcamps. They help clarify complex concepts, assist with coding exercises, answer student questions, and sometimes grade assignments or provide feedback. TAs often have a strong foundation in programming, statistics, and data analysis, and they play a key role in enhancing the learning experience. Their involvement can range from leading small group sessions to providing one-on-one help during office hours.

What skills and qualifications are needed to be a data science teaching assistant?

To thrive as a Data Science Teaching Assistant, you need a solid understanding of data science concepts, programming (especially Python or R), statistics, and often a relevant degree or coursework. Familiarity with tools such as Jupyter Notebooks, data visualization libraries, and version control systems like Git is typically required. Strong communication, patience, and the ability to explain complex topics clearly are standout soft skills in this role. These skills enable effective student support, reinforce learning outcomes, and contribute to a positive educational environment.

What challenges do data science teaching assistants face when supporting student learning, and how can they be addressed?

Data Science Teaching Assistants often encounter challenges such as explaining complex concepts in accessible ways, managing diverse student skill levels, and providing timely feedback on assignments. To address these challenges, it's important to use clear examples, encourage open communication, and adapt explanations to different learning styles. Collaborating closely with course instructors and leveraging office hours or online discussion forums can also help TAs support students more effectively and ensure no one falls behind.

What is the difference between Data Science Teaching Assistant vs Data Analyst?

AspectData Science Teaching AssistantData Analyst
Required CredentialsOften a degree in data science, statistics, or related field; familiarity with data toolsDegree in statistics, data analysis, or related field; proficiency in data tools
Work EnvironmentEducational settings, labs, online coursesBusiness, corporate, or research environments
Employer & Industry UsageUniversities, online education platformsCorporations, consulting firms, government agencies
Common Search & Comparison IntentUnderstanding teaching roles in data science educationUnderstanding data analysis tasks and roles

While both roles involve working with data and require similar technical skills, a Data Science Teaching Assistant primarily supports educational activities, assisting instructors and students in learning data science concepts. In contrast, a Data Analyst focuses on analyzing data to generate insights for business decisions. The roles differ mainly in their work environment and primary objectives, though they share foundational data skills.

How to become a data science teaching assistant?

To become a data science teaching assistant, candidates typically need a strong background in data science, statistics, or related fields, along with proficiency in programming languages like Python or R. Relevant experience with data analysis, machine learning, and teaching or mentoring skills are also important, and some positions may require a graduate degree or teaching experience. Gaining familiarity with tools such as Jupyter notebooks and SQL can enhance qualifications.

What are popular job titles related to Data Science Teaching Assistant jobs in Pennsylvania?

For Data Science Teaching Assistant jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Data Science Teaching Assistant jobs in Pennsylvania look for?

The top searched job categories for Data Science Teaching Assistant jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Data Science Teaching Assistant jobs?

Cities in Pennsylvania with the most Data Science Teaching Assistant job openings:

Data Science Teaching Assistant jobs near you
Infographic showing various Data Science Teaching Assistant job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, 3% Contract, and 1% Nights. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

AI & Data Science Intern

Carlisle Companies, Inc.

Carlisle, PA • On-site

Full-time

Re-posted yesterday

Job description

The AI & Data Science Engineering Intern will support cutting-edge projects at the intersection of software engineering, applied AI, and materials innovation. The intern will work on initiatives that combine agentic AI workflows, computer vision, and data science to accelerate research and development in construction materials. The role includes building end-to-end prototypes that integrate backend services, AI models, and user interfaces to drive digital transformation across the organization.
Duties and Responsibilities:
  • Assist in the design and development of agentic AI workflows, integrating large language models with data sources and multi-agent orchestration.
  • Develop and maintain backend APIs and services using frameworks such as FastAPI to support AI and data science applications.
  • Build interactive dashboards and prototypes with Streamlit, Reflex, or similar tools for internal stakeholders.
  • Contribute to computer vision workflows, such as SEM image analysis and defect detection, to automate materials characterization.
  • Perform data wrangling, exploratory analysis, and statistical modeling to uncover insights from experimental, operational, and customer datasets.
  • Collaborate with the team to design, implement, and test machine learning models (regression, clustering, NLP, computer vision).
  • Document methodologies, maintain reproducible codebases, and present results to both technical and business stakeholders.
  • Stay current with emerging tools, frameworks, and best practices in agentic AI, software engineering, computer vision, and data science.

Qualification:
  • Currently pursuing a Master's or PhD in Computer Science, Data Science, Engineering, or a related field from an accredited university with a minimum 3.0 GPA.
  • Strong programming skills in Python with experience in libraries such as pandas, scikit-learn, OpenCV, TensorFlow/PyTorch.
  • Experience with backend frameworks (FastAPI, Flask, Django) and frontend/UI tools (Streamlit, Reflex, React-based).
  • Familiarity with LLMs, agentic AI frameworks, or orchestration tools (LangChain, LlamaIndex, or custom pipelines).
  • Solid understanding of machine learning and computer vision principles.
  • Interest in applying AI/ML to industrial and materials science challenges.

Additional Information:
Work Location: Carlisle, PA. No travel required. Remote work is not available for this position.
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