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Part Time Data Science Instructor Jobs in Toronto, ON

City of Toronto

PROGRAM EVALUATOR

Toronto, ON · On-site

CA$52.38 - CA$57.39/hr

Master's degree in Health Sciences, Applied Social Sciences, Health Administration or an equivalent ... NOTE TO INTERNAL FULL-TIME AND PART-TIME CITY OF TORONTO EMPLOYEES: City of Toronto employees must ...

Baycrest

Research Programmer

Toronto, ON · Hybrid

CA$82/hr

Data entry and data correction. * Performs IT-Technician duties, as required, or as needs arise ... Bachelor degree in Computer Science. Required skills/experience: * Skilled in Python, HTML, Apache ...

BMO Capital Markets

Tech Lead, AI Engineering

Toronto, ON · Hybrid

CA$75K - CA$141K/yr

Integrates data from multiple sources (structured and unstructured) while addressing security ... Experience & Education * University degree in Computer Science, Engineering * 8+ years of ...

BMO Capital Markets

AI CyberSecurity Architect

Toronto, ON · On-site

CA$103K - CA$192K/yr

Data ingestion and preprocessing * Model training and tuning * Deployment and inference layers ... Bachelor's Degree in Engineering or Computer Science or relevant discipline * 10+ years overall ...

Maple Leaf Foods

FSQA Process Leader

Hamilton, ON

CA$47K - CA$69K/yr

For part-time roles, salaries are adjusted according to scheduled hours.??Snapshot of a Day-in-the ... Ability to enter data and complete trace exercises within SAP.Identification, entry and closure of ...

Humber River Health

Pathology Assistant II

Toronto, ON · On-site

CA$44.77 - CA$56/hr

Permanent Part Time Hours of Work: 8 hour rotating shifts from Monday - Friday, including weekends ... Qualifications: * Undergraduate Degree in Science and/or related discipline required.

Humber River Health

Physiotherapist

Toronto, ON · On-site

CA$40.36 - CA$56.30/hr

Permanent Part-Time Reporting Relationship: Manager of Allied Health Hourly Rate Range: $40.36 ... Record workload measurement data in a timely and precise manner. * Collaborate as an integral ...

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Part Time Data Science Instructor information

See Toronto, ON salary details

$9

$48

$110

How much do part time data science instructor jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for part time data science instructor in Toronto, ON is $48.81, according to ZipRecruiter salary data. Most workers in this role earn between $21.11 and $62.63 per hour, depending on experience, location, and employer.

What does a part time data science instructor do?

A Part Time Data Science Instructor teaches data science concepts and skills to students, typically in a classroom or online setting, on a part-time basis. Their responsibilities include preparing lesson plans, delivering lectures or workshops, guiding students through practical exercises, and providing feedback on assignments. They often cover topics such as statistics, programming (usually Python or R), machine learning, and data analysis. Instructors may also help students with career advice and project-based learning. The part-time nature of the role allows for flexibility and may attract industry professionals who want to share their expertise while maintaining other commitments.

What are some common challenges faced by part time data science instructors, and how can they be addressed?

Part-time data science instructors often juggle teaching responsibilities alongside other professional commitments, which can make time management a challenge. Staying current with rapidly evolving tools and techniques in data science is also essential, as students expect instruction on the latest industry practices. Building engagement and fostering interaction in limited class hours can require creative lesson planning and use of real-world projects. To address these challenges, instructors benefit from leveraging collaborative curriculum resources, actively participating in professional development, and maintaining open communication with students and fellow faculty.

What are the key skills and qualifications needed to thrive as a part time data science instructor, and why are they important?

To thrive as a Part Time Data Science Instructor, you need a strong background in statistics, programming (commonly Python or R), and data analysis, typically supported by a relevant degree or industry experience. Familiarity with technical tools such as Jupyter Notebooks, machine learning libraries (like scikit-learn or TensorFlow), and data visualization platforms is essential, and teaching certifications can be advantageous. Outstanding communication, adaptability, and the ability to simplify complex concepts help instructors engage and support diverse learners. These skills and qualities are crucial for delivering effective instruction, fostering student understanding, and ensuring positive learning outcomes.
Part Time Data Science Instructor jobs near you
Infographic showing various Part Time Data Science Instructor job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $101,517 per year, or $48.8 per hour.

Lead Agentic Solutions Architect

Band of Coders

Toronto, ON • Remote

Part-time

Posted 22 days ago

Job description

Location: Remote (USA or Canada strongly preferred; Americas time zones required)

About the Role

At Band of Coders, we are pushing the boundaries of automation and intelligence. We are looking for a Lead Agentic Solutions Architect who combines deep AI engineering expertise with exceptional client-facing leadership.

In this high-impact role, you won't just build—you will consult, lead, and sell. You will partner directly with client executives to translate complex operational challenges into autonomous AI workflows, join sales calls as the technical authority to win new business, and mentor our engineering teams in delivering robust, scalable AI architectures.

Initially, this will be an hourly contractor position, part-time.

Key Responsibilities

1. Client Leadership & Sales Engineering

  • Pre-Sales & Discovery: Join pre-sales calls with prospects and clients as the primary technical authority to scope opportunities, build trust, and demonstrate technical capability.
  • Technical Consultation: Translate business problems into actionable, state-of-the-art agentic architectures for non-technical stakeholders and executive teams.
  • Solution Pitching: Partner with the sales and growth teams to craft compelling technical proposals, proofs-of-concept (POCs), and architecture roadmaps.

2. Architecture, Workflow & Automation

  • Design, implement, and maintain advanced agentic processes, multi-agent systems, and automated workflows.
  • Develop and enforce mandatory monitoring workflows, systematic data cross-checks, and guardrails to ensure production-grade reliability.
  • Bridge the gap between raw AI processor capabilities and practical, high-value client operations.

3. Team Leadership & Strategic Guidance

  • Lead and mentor engineering teams through the execution of agentic integrations.
  • Establish best practices for multi-provider routing, Model Context Protocol (MCP) implementations, and LLM monitoring.
  • Serve as the principal technical liaison between Band of Coders leadership, our clients, and our execution teams.


Requirements & Qualifications

Leadership & Communication (Must-Haves)

  • Client-Facing & Sales Experience: Proven track record in a client-facing role (e.g., Solutions Architect, Technical Consultant, Sales Engineer, or Founder/Fractional CTO) with active involvement in pre-sales strategy and technical discovery.
  • Exceptional Communication: Fluent verbal and written English with a demonstrated ability to explain complex LLM and agentic concepts clearly to C-suite executives, non-technical clients, and developers alike.
  • Time Zone Alignment: Located in North America (USA or Canada strongly preferred), or working within US/Canada business hours (EST/PST).
  • Technical Leadership: Experience leading technical teams, driving architectural decisions, and owning client deliverables end-to-end.

Deep AI & Technical Expertise

  • State-of-the-Art LLMs & Frontier Models: Experience optimizing and routing across multi-provider environments including OpenAI (GPT-4o/o1/o3), Anthropic (Claude 3.5 Sonnet/Opus), and open-weight models (Llama 3, Mistral).
  • Agentic Frameworks & Ecosystems: Hands-on experience with orchestration frameworks such as LangGraph, CrewAI, PydanticAI, Hugging Face smolagents, or cloud-native toolkits (Google ADK, OpenAI Agents SDK).
  • Model Context Protocol (MCP): Practical experience implementing or building custom MCP servers (e.g., GitHub, Playwright, PostgreSQL/Supabase, Filesystem, or Enterprise API connectors) to decouple reasoning from execution.
  • Structured Outputs & Function Calling: Strong mastery of JSON schema enforcement, tool definition, and prompt optimization via tools like DSPy or Instructor.
  • Vector DBs & RAG Tools: Knowledge of state retention and retrieval using Pinecone, Milvus, or pgvector.
  • Cloud & Infrastructure: Hands-on experience designing and deploying scalable environments across AWS, GCP, or Azure.