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Data Science Teaching Assistant Jobs in Calgary, AB

KEY RESPONSIBILITIES Data Science & AI Solutions * Develop and deploy statistical, machine learning ... assistants. * Experience with Azure OpenAI, Databricks, MLflow, Azure AI, or similar cloud-based AI ...

KEY RESPONSIBILITIES Data Science & AI Solutions * Develop and deploy statistical, machine learning ... assistants. * Experience with Azure OpenAI, Databricks, MLflow, Azure AI, or similar cloud-based AI ...

... * Assist with data quality, system enhancements, and continuous improvement projects. What You'll Bring * Degree in Computer Science, Information Systems, Data Science, Business, or a related field.

Support cross functional stakeholders with scalable reporting architecture * Assist in high ... Bachelor's Degree (Computer Science, Technology, Engineering, or related field) * 10+ years of ...

Support consultants will work as part of the CDST to assist clients facing teams with data ... Bachelors or Diploma in Computer Science, Database Management, Data Programming, Information ...

... power of scientific testing and data-driven insights to build a healthier future. About the ... General laboratory clean-up and maintenance; * Assist in sample flow and archiving as well as data ...

Forward Deployed Product Manager

Calgary, AB ยท Remote

CA$110K - CA$150K/yr

Bachelor's degree in Computer science, Engineering, Data Science, or related fields. * Experience ... Demonstrated daily experience using AI coding assistants, generative tools, and automated workflows ...

Manager, Machine Learning Engineering

Calgary, AB ยท Remote

CA$181K - CA$272K/yr

... operations, and data science to identify new tooling for ML and LLM-driven features for Clio ... Teach and learn from those around you, providing constructive feedback and taking on feedback to ...

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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 job categories do people searching Data Science Teaching Assistant jobs in Calgary, AB look for?

The top searched job categories for Data Science Teaching Assistant jobs in Calgary, AB are:

What cities near Calgary, AB are hiring for Data Science Teaching Assistant jobs?

Cities near Calgary, AB with the most Data Science Teaching Assistant job openings:

Infographic showing various Data Science Teaching Assistant job openings in Calgary, AB as of June 2026, with employment types broken down into 89% Full Time, 10% Part Time, and 1% Contract. Highlights an 80% Physical, 2% Hybrid, and 18% Remote job distribution.

Data Scientist

NRG Energy

Calgary, AB โ€ข On-site

Full-time

Posted 7 days ago


Job description

Welcome to the intersection of energy and home services. At Direct Energy, an NRG company, we're all about propelling the next generation of leaders forward. We are driven by our passion to create a smarter, cleaner and more connected future. We deliver innovative solutions that make our customers' lives easier-helping them power, protect, and intelligently manage their homes and businesses. To do this, we need creative and talented people to join our company.

We offer a dynamic work environment and a unified and inclusive culture. Our company programs are designed to help employees develop the skills they need for success now and in the future. In everything we do, we aim to champion our employees and bring value to our customers, investors and society.

More information is available at www.directenergy.com. Connect with NRG and Direct Energy on Facebook, LinkedIn, and follow us on Twitter.

JOB SUMMARY:ย 

The Data Scientist, Customer Care Analytics is responsible for developing, validating, deploying, and monitoring advanced analytical, machine learning, and Generative AI solutions that improve customer outcomes, operational performance, employee productivity, and business decision-making.

This role partners closely with Customer Care, Collections, Billing, Workforce Management, Technology, and Business Leadership teams to transform data into actionable insights and scalable solutions. The successful candidate will identify opportunities to leverage reporting, advanced analytics, predictive modeling, optimization, Large Language Models (LLMs), and other AI technologies to address complex business challenges.

The role is accountable for the end-to-end lifecycle of analytical and AI solutions, including business problem definition, data acquisition, model development, validation, deployment, monitoring, governance, and business adoption. In addition to advanced analytical work, the role will contribute to reporting, dashboarding, and decision-support solutions that enable data-driven decision-making across Customer Care operations. The role aligns well with the capabilities of advanced analytics, machine learning, model monitoring, validation, and decision-support solutions described within existing enterprise analytics practices.

ย 

KEY RESPONSIBILITIES

Data Science & AI Solutions

  • Develop and deploy statistical, machine learning, forecasting, optimization, and Generative AI solutions that improve customer outcomes and operational performance.
  • Translate business problems into analytical approaches and actionable recommendations.
  • Evaluate when reporting, advanced analytics, machine learning, or LLM-based solutions are the most appropriate approach.

Model Development, Validation & Monitoring

  • Design, build, validate, and maintain predictive, forecasting, and AI models.
  • Establish model performance standards, monitoring frameworks, and governance controls.
  • Identify model drift, performance degradation, and opportunities for retraining or enhancement.

Data & Technical Delivery

  • Acquire, integrate, and prepare data from multiple sources for analytical and AI applications.
  • Develop scalable analytical workflows, data pipelines, and reusable data assets using modern analytics tools and platforms.
  • Apply best practices for testing, documentation, version control, and deployment.

Business Partnership & Innovation

  • Partner with business leaders and stakeholders to identify opportunities for analytics and AI to create business value.
  • Communicate analytical findings and recommendations to technical and non-technical audiences.
  • Evaluate emerging technologies and drive innovation through advanced analytics, AI, and automation initiatives.

Reporting & Decision Support

  • Develop dashboards, reports, scorecards, and data visualizations that support operational and strategic decision-making.
  • Translate analytical outputs into clear business insights and performance measures.
  • Ensure reporting accuracy, consistency, and alignment with business definitions.

Minimum Qualifications

  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or related quantitative discipline.
  • 3+ years of experience in Data Science, advanced analytics, machine learning, forecasting, or related analytical roles.
  • Experience developing predictive, forecasting, optimization, or statistical models in a business environment.
  • Strong proficiency with SQL and Python.
  • Experience working with large and complex datasets.
  • Experience applying statistical analysis and quantitative problem-solving techniques.
  • Experience communicating analytical findings to non-technical stakeholders.
  • Experience developing dashboards or reports using Power BI, Tableau, or similar tools.

Preferred Qualifications:

  • Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI assistants.
  • Experience with Azure OpenAI, Databricks, MLflow, Azure AI, or similar cloud-based AI platforms.
  • Strong understanding of statistics, machine learning, forecasting, and Generative AI technologies.
  • Experience with model validation, model governance, and model monitoring practices.
  • Experience with forecasting, optimization, contact center analytics, workforce management, collections, or customer care operations.
  • Experience deploying and supporting production machine learning solutions.
  • Knowledge of responsible AI, model explainability, and AI governance principles.

Additional Knowledge, Skills & Abilities

  • Ability to determine the most appropriate solution approach, whether reporting, analytics, machine learning, optimization, or AI.
  • Strong business acumen and problem-solving skills.
  • Excellent communication, data storytelling, and presentation skills.
  • Strong technical writing and documentation capabilities.
  • Ability to manage multiple priorities in a fast-paced environment.
  • Continuous learning mindset with interest in emerging AI and analytics technologies.
ย 

NRG Energy is committed to a drug and alcohol-free workplace. To the extent permitted by law and any applicable collective bargaining agreement, employees are subject to periodic random drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F/Vet/Disability. Level, Title and/or Salary may be adjusted based on the applicant's experience or skills. ย 

Official description on file with Talent.

We support the use of AI tools to help you prepare for your interview (e.g., practicing responses, researching the role, or refining your resume). However, during interviews and assessments, we expect responses to reflect your own thinking, experience, and communication. Use of AI to generate or read answers in real time, complete assessments, or misrepresent your qualifications is not permitted and may impact your candidacy.


NRG logo

About NRG

Sourced by ZipRecruiter

At NRG, we're bringing the power of energy to people and organizations by putting customers at the center of everything we do. We generate electricity and provide energy solutions and natural gas to millions of customers through our diverse portfolio of retail brands. A Fortune 500 company, operating in the United States and Canada, NRG delivers innovative solutions while advocating for competitive energy markets and customer choice, working towards a sustainable energy future. More information is available at www.nrg.com. Connect with NRG on Facebook, LinkedIn and follow us on Twitter @nrgenergy.

Industry

Oil and coal products manufacturing

Company size

5,001 - 10,000 Employees

Headquarters location

Houston, TX, US