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Data Science Teaching Assistant Jobs in Raleigh, NC

North Carolina Jobs

Instructional Assistant

Raleigh, NC · On-site

Instructional Assistant JOB STATUS: Full-Time/10-Month LOCATION: Claxton Elementary School CONTACT ... Score students' papers as instructed by the teacher. * Checks and reports attendance. * Files data ...

Kanak Elite Services Inc

Data and AI Analyst

Cary, NC · On-site

AI & Machine Learning • Assist in building and monitoring AI models using SAS Viya and other ... Qualifications • Bachelor's degree in Data Science, Computer Science, Statistics, Public Policy ...

Clever Devices Ltd.

Associate

Apex, NC · On-site

$70K - $75K/yr

The Associate, Data Science will perform data analysis of Clever Devices customers related to ... * Assist in writing programs to cleanse data with the purpose of integrating it into operations in ...

Varsity Tutors

ACT Science Tutor

Raleigh, NC · Remote

$18 - $40/hr

Advanced Scientific Reasoning Mastery: Deep knowledge of data representation (graphs, tables ... Strategic Data Analysis & Reasoning: Skilled at teaching quick graph reading, variable ...

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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 Raleigh, NC? For Data Science Teaching Assistant jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Data Science Teaching Assistant jobs in Raleigh, NC look for? The top searched job categories for Data Science Teaching Assistant jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Data Science Teaching Assistant jobs? Cities near Raleigh, NC with the most Data Science Teaching Assistant job openings:
Data Science Teaching Assistant jobs near you
Data Analytics Business Analyst (Full-Time Remote, North Carolina)

Data Analytics Business Analyst (Full-Time Remote, North Carolina)

Alliance

Morrisville, NC • On-site, Remote

$81K - $104K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 27 days ago

Job description

The Data Analytics Business Analyst gathers and documents business and technical needs for data and analytics projects, converts them into analytical specifications and test plans, assists in building and validating dashboards, reports, and predictive models, and safeguards data quality and HIPAA compliance across all analytical solutions.
This position is full-time remote. Selected candidate must reside in North Carolina and be willing to travel to the home office (Morrisville, NC) for onsite team meetings as needed.
Responsibilities & Duties
Elicit and Document Analytics Requirements
  • Lead discovery meetings to capture business objectives, key performance indicators (KPIs), and reporting needs
  • Capture data source requirements, frequency, granularity, and any service level expectations (e.g., refresh windows)
  • Produce requirements artifacts such as Business Requirements Documents (BRDs), data modeling diagrams, and acceptance criteria that define the desired analytics outcomes
  • Analyze and Profile Data Perform data profiling on source systems (e.g., relational databases, data lakes, SaaS APIs) to understand completeness, consistency, and distribution of fields
  • Conduct gap analysis to identify missing attributes or mismatches against reporting specifications
  • Document data quality issues, propose validation rules, and define reconciliation procedures that support accurate analytics

Translate Requirements into Analytical Specifications
  • Develop detailed functional and technical specifications for data models, dimensional schemas (star/snowflake), and analytical pipelines (ETL/ELT, data wrangling scripts, BI tool configurations)
  • Collaborate with data engineers, data scientists, and BI developers to align design patterns, naming conventions, and reusable components
  • Ensure specifications address scalability, security (including HIPAA related data handling), and maintainability of analytical solutions

Plan and Execute Testing of Analytical Solutions
  • Create test plans, test cases, and validation data sets for unit, integration, and user acceptance testing of dashboards, reports, and predictive models
  • Support business stakeholders with UAT; log defects, prioritize fixes, and oversee retesting cycles
  • Verify performance (e.g., query response time, model runtime) against agreed upon thresholds

Support Implementation and Ongoing Operations
  • Assist with go live activities such as preparation of runbooks, standard operating procedures (SOPs), and cut over checklists for analytics releases
  • Monitor initial production runs, perform data reconciliations, and address any discrepancies that arise
  • Participate in incident response, root cause analysis, and documentation of lessons learned for continuous improvement

Maintain Documentation and Knowledge Base
  • Keep current inventories of data sources, data dictionaries, lineage diagrams, and model documentation up to date
  • Author and refresh end user guides, technical "how to" documents, and metadata catalogs in line with departmental standards

Communication and Collaboration
  • Translate complex analytical concepts into clear language for both technical and non technical audiences
  • Partner with internal business units, external data providers, and vendor teams to ensure alignment on data definitions, delivery schedules, and reporting expectations
  • Contribute to data governance initiatives, supporting standards for data stewardship, privacy, and compliance

Continuous Improvement
  • Identify opportunities to streamline analytics workflows through reusable templates, automation (e.g., CI/CD pipelines for data models), and self service tooling
  • Define and track analytics related KPIs such as report delivery timeliness, data quality error rates, and model accuracy
  • Recommend best practice enhancements to increase efficiency, data reliability, and user satisfaction

Minimum Requirements
Education and Experience
Vocational or Technical Training in in Computer Science, Information Systems, Business Administration, or a related field; and six (6) years of experience in data analytics or data science;
Or
Associate's degree from an accredited university in Computer Science, Information Systems, Business Administration, or a related field; and five (5) years of experience in data analytics or data science;
Or
Bachelor's degree from an accredited university in Computer Science, Information Systems, Business Administration, or a related field; and five (3) years of experience in data analytics or data science.
Knowledge, Skills, & Abilities
  • SQL (preferably T-SQL)
  • Communication skills
  • Data Visualization Tools
  • Software Development Life Cycle (SDLC)
  • Data Governance
  • Documentation Tools and Platforms

Employment for this position is contingent upon a satisfactory background check and credit check, which will be performed after acceptance of an offer of employment and prior to the employee's start date.
Salary Range
$81,873-104,388/Annually
Exact compensation will be determined based on the candidate's education, experience, external market data and consideration of internal equity.
An excellent fringe benefit package accompanies the salary, which includes:
  • Medical, Dental, Vision, Life, Long and Short-Term Disability
  • Generous retirement savings plan
  • Flexible work schedules including hybrid/remote options
  • Paid time off including vacation, sick leave, holiday, management leave
  • Dress flexibility

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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