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Data Science Teaching Assistant Jobs in Rochester, NY

Conceptual Teaching & Problem-Solving: Skilled at breaking down the scientific method, experimental variable identification, and basic data analysis for middle school learners. Guides students ...

Earth Science Tutor

Rochester, NY · Remote

$18 - $40/hr

Adapts instruction using rock and mineral samples, weather data analysis, and interactive mapping tools to support middle and high school students building scientific literacy. * Effective Teaching ...

Python Tutor

Rochester, NY · Remote

$18 - $40/hr

... for data science, web development, automation, and computer science coursework. * Conceptual Teaching & Problem-Solving: Skilled at breaking down algorithm design, data manipulation, and object ...

... data analysis methods while preparing students for AP science courses, Regents examinations, and college science prerequisites. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ...

... data structures while preparing students for the AP Computer Science A examination including multiple-choice and free-response questions. * Conceptual Teaching & Problem-Solving: Skilled at teaching ...

Business Data Analyst

Rochester, NY · On-site

$27.90 - $29.80/hr

Query data from a variety of systems to produce data sets for analysis. * Assist in the preparation ... Bachelor's degree in applied mathematics, Statistics, Data Science or a related field is preferred.

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Data Science Teaching Assistant information

What are the key skills and qualifications needed to thrive as a Data Science Teaching Assistant, and why are they important?

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 are the most common challenges faced by Data Science Teaching Assistants 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 are Data Science Teaching Assistants?

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 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.

What are popular job titles related to Data Science Teaching Assistant jobs in Rochester, NY? For Data Science Teaching Assistant jobs in Rochester, NY, the most frequently searched job titles are:
What job categories do people searching Data Science Teaching Assistant jobs in Rochester, NY look for? The top searched job categories for Data Science Teaching Assistant jobs in Rochester, NY are:
What cities near Rochester, NY are hiring for Data Science Teaching Assistant jobs? Cities near Rochester, NY with the most Data Science Teaching Assistant job openings:
Sustainability Data & Reporting Analyst

Sustainability Data & Reporting Analyst

CooperVision

Victor, NY • On-site

Full-time

Posted 22 days ago


CooperVision rating

7.2

Company rating: 7.2 out of 10

Based on 12 frontline employees who took The Breakroom Quiz


Job description

Job Summary:
CooperVision is a leading global manufacturer of contact lenses dedicated to improving vision. The Sustainability Data & Reporting Analyst will support the collection and reporting of sustainability-related data, focusing on accuracy and consistency for internal and external disclosures.
Responsibilities:
• Collect, consolidate, and validate sustainability-related data from multiple internal systems, ensuring consistency, accuracy, and alignment to reporting requirements
• Work with IT to support data integration, transformation, and flow into reporting systems
• Support the preparation and maintenance of standardized data templates and assist in transforming data into formats required for sustainability reporting systems
• Support the delivery of accurate and timely sustainability reporting aligned to internal and external requirements
• Assess and validate that evolving sustainability data requirements (e.g., regulatory changes, transition from estimated to actual data) are supported by existing data structures and reporting systems
• Support and coordinate user acceptance testing (UAT) activities, ensuring sustainability data outputs are aligned with business requirements and validated prior to reporting and downstream use
• Identify and resolve data quality issues (e.g., inconsistencies, missing data, and unit conversions) and document data sources, processes, and assumptions to support transparency and audit readiness
• Support the ongoing monitoring and validation of sustainability data, helping ensure quality issues are identified and resolved proactively to maintain audit readiness and reporting accuracy
• Collaborate with cross-functional teams (e.g., EHS, IT, procurement, facilities, packaging engineering, and operations) to understand data sources and improve data collection, traceability, and consistency
• Support efforts to improve and automate sustainability data collection processes to reduce manual effort and increase scalability
• Support the collection, structuring, and validation of packaging and material composition data required for emerging regulatory requirements (e.g. EPR, recyclability, plastics disclosure)
• Assist in mapping sustainability and packaging-related data to evolving regulatory and reporting requirements across global jurisdictions
• Support the development of scalable data structures and governance processes for sustainability data
Qualifications:
Required:
• Bachelor’s degree in a related field required (Data Analytics, Data Science, Environmental Science or Sustainability, Information Systems, Engineering, etc.)
• 1-3 years of experience supporting data analysis, reporting, or equivalent relevant internship experience.
• Experience working with data tools such as Tableau, Excel, or similar platforms is required.
• Strong analytical and problem-solving skills with the ability to work with structured and unstructured data
• Hands-on experience with data visualization tools such as Tableau (required)
• Proficiency in Microsoft Excel, including data manipulation and analysis
• Foundational understanding of data structures, data flows, and data governance principles
• Strong attention to detail, particularly when working with data accuracy and transformation
• Experience working across multiple systems and identifying relevant data sources (e.g., ERP, financial, or operational systems) to support data analysis and reporting
• Comfortable operating in a dynamic environment with evolving data requirements and changing business needs
• Strong verbal and written communication skills, with the ability to explain data concepts to non-technical stakeholders
• Demonstrated ability to manage multiple tasks and priorities in a fast-paced environment
• Capable of working independently once priorities are defined, with a proactive approach to problem-solving
Preferred:
• Familiarity with sustainability, environmental science, or ESG reporting concepts (e.g., Scope 1, 2, 3)
• Exposure to product, packaging, or material data within enterprise or ERP systems
• Exposure to ERP systems (e.g., Oracle, SAP, Baan) and understanding of how transactional data is structured and sourced
• Understanding of data quality challenges related to sustainability or regulatory reporting
• Experience using SQL, Python, or similar tools for data analysis or preparation
• Experience working with large or complex datasets across multiple systems
• Familiarity with enterprise systems or data pipelines
• Internship or academic project experience involving real-world data analysis
Company:
CooperVision is one of the world’s leading manufacturers of soft contact lenses and related products and services. It is a sub-organization of The Cooper Companies. Founded in 1980, the company is headquartered in Fairport, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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