Data Scientist III
- Toronto, ON, Canada
$63.02 to $69.88 CAD / hour
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Job details
- Pay
- $63.02 to $69.88 CAD / hour
- Apply by
- Experience
- Applied Data Science Depth: 5+ years of dedicated professional experience developing and deploying machine learning models and statistical solutions in an enterprise setting.
- Posting language
- English
- Posted
Original job description
Our client, is seeking an experienced, highly innovative Data Scientist III (Senior Data Science & GenAI / Agentic AI Specialist) to join their centralized Advanced Analytics team.
In this strategic, hands-on role, you will partner directly with business units across Canada to accelerate the adoption and execution of advanced analytics, machine learning, and Generative AI solutions. You will translate complex business goals into rigorous analytical frameworks, building predictive models alongside cutting-edge GenAI applications, AI agents, and autonomous systems. Working in a hybrid environment, you will leverage Python, PySpark, SQL, vector databases, and modern agentic frameworks (LangChain, LangGraph, CrewAI) to design Retrieval-Augmented Generation (RAG) architectures, prompt engineering pipelines, and intelligent information retrieval systems that drive measurable commercial value.
Duration: 12-Month Contract (Full 1-Year Engagement)
Work Arrangement: Hybrid (3 days on-site per week; Thursday set as the mandatory team collaboration anchor day)
Advantages
High-Impact AI Innovation Scope: Lead the design, development, and deployment of next-generation GenAI solutions, autonomous AI agents, and custom RAG architectures.
12-Month Engagement Stability: Secure a full 1-year enterprise consulting assignment driving strategic, high-visibility analytics initiatives across enterprise business units.
Modern Agentic Tech Stack: Work extensively with state-of-the-art AI frameworks (LangChain, LangGraph, CrewAI), vector databases, embedding models, and reasoning tools.
Collaborative Leadership Culture: Mentor junior data scientists and data engineers while presenting data-driven insights and commercial recommendations to cross-functional business executives.
Responsibilities
Data Science & ML Engineering: Translate complex business problems into analytical models; design, train, evaluate, and deploy supervised, unsupervised, and predictive machine learning models.
GenAI & Agentic AI Development: Design, build, and deploy production-grade GenAI solutions, AI bots, and autonomous agents featuring advanced reasoning, tool-use patterns, and multi-agent coordination.
RAG & Vector Search Architecture: Implement RAG (Retrieval-Augmented Generation) systems, vector database indexing, embedding models, and prompt engineering strategies to enable intelligent enterprise search capabilities.
Big Data & Pipeline Integration: Write complex PySpark and SQL queries to extract, transform, and integrate large-scale structured and unstructured datasets across enterprise data sources.
Technical Artifacts & Governance: Author and maintain technical design documentation covering application functionality, data models, microservice APIs, and system integration patterns.
Stakeholder Storytelling & Mentorship: Present analytical findings and strategic recommendations to senior business leaders through concise data storytelling, while mentoring junior data scientists and engineers.
Qualifications
Education: Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative discipline (or equivalent practical experience).
Applied Data Science Depth: 5+ years of dedicated professional experience developing and deploying machine learning models and statistical solutions in an enterprise setting.
Core Technical Proficiency: Expert-level mastery of Python for data science and LLM application development, alongside strong SQL and PySpark data extraction and manipulation skills.
GenAI & Agentic Frameworks: Demonstrated hands-on experience building GenAI applications using frameworks such as LangChain, LangGraph, or CrewAI, with proven knowledge of tool-calling and reasoning agent patterns.
RAG & LLM Engineering: Deep understanding of RAG techniques, prompt engineering, vector databases, embedding models, and fine-tuning methodologies.
Structured & Unstructured Data: Solid background in feature engineering, data transformation, and managing both structured databases and unstructured content streams.
Communication & Mentorship: Exceptional written and verbal communication skills with a proven track record of translating complex AI concepts into executive business narratives and coaching team members.
Preferred Assets & Nice-to-Haves
Hands-on experience with AWS AI/ML services (SageMaker, AWS Bedrock, Lambda).
Familiarity with enterprise data warehousing and big data pipeline tools (AWS Glue ETL, Glue Catalog, Glue Data Quality, and AWS Step Functions).
Summary
If you are a tech-savvy Data Scientist III who pairs 5+ years of core machine learning mastery with hands-on GenAI, agentic AI frameworks (LangChain/LangGraph), PySpark, and RAG architecture skills, this 12-month hybrid contract opportunity is an ideal next step. Bring your analytical curiosity, agentic AI expertise, and technical leadership to our client's team today!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
In this strategic, hands-on role, you will partner directly with business units across Canada to accelerate the adoption and execution of advanced analytics, machine learning, and Generative AI solutions. You will translate complex business goals into rigorous analytical frameworks, building predictive models alongside cutting-edge GenAI applications, AI agents, and autonomous systems. Working in a hybrid environment, you will leverage Python, PySpark, SQL, vector databases, and modern agentic frameworks (LangChain, LangGraph, CrewAI) to design Retrieval-Augmented Generation (RAG) architectures, prompt engineering pipelines, and intelligent information retrieval systems that drive measurable commercial value.
Duration: 12-Month Contract (Full 1-Year Engagement)
Work Arrangement: Hybrid (3 days on-site per week; Thursday set as the mandatory team collaboration anchor day)
Advantages
High-Impact AI Innovation Scope: Lead the design, development, and deployment of next-generation GenAI solutions, autonomous AI agents, and custom RAG architectures.
12-Month Engagement Stability: Secure a full 1-year enterprise consulting assignment driving strategic, high-visibility analytics initiatives across enterprise business units.
Modern Agentic Tech Stack: Work extensively with state-of-the-art AI frameworks (LangChain, LangGraph, CrewAI), vector databases, embedding models, and reasoning tools.
Collaborative Leadership Culture: Mentor junior data scientists and data engineers while presenting data-driven insights and commercial recommendations to cross-functional business executives.
Responsibilities
Data Science & ML Engineering: Translate complex business problems into analytical models; design, train, evaluate, and deploy supervised, unsupervised, and predictive machine learning models.
GenAI & Agentic AI Development: Design, build, and deploy production-grade GenAI solutions, AI bots, and autonomous agents featuring advanced reasoning, tool-use patterns, and multi-agent coordination.
RAG & Vector Search Architecture: Implement RAG (Retrieval-Augmented Generation) systems, vector database indexing, embedding models, and prompt engineering strategies to enable intelligent enterprise search capabilities.
Big Data & Pipeline Integration: Write complex PySpark and SQL queries to extract, transform, and integrate large-scale structured and unstructured datasets across enterprise data sources.
Technical Artifacts & Governance: Author and maintain technical design documentation covering application functionality, data models, microservice APIs, and system integration patterns.
Stakeholder Storytelling & Mentorship: Present analytical findings and strategic recommendations to senior business leaders through concise data storytelling, while mentoring junior data scientists and engineers.
Qualifications
Education: Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative discipline (or equivalent practical experience).
Applied Data Science Depth: 5+ years of dedicated professional experience developing and deploying machine learning models and statistical solutions in an enterprise setting.
Core Technical Proficiency: Expert-level mastery of Python for data science and LLM application development, alongside strong SQL and PySpark data extraction and manipulation skills.
GenAI & Agentic Frameworks: Demonstrated hands-on experience building GenAI applications using frameworks such as LangChain, LangGraph, or CrewAI, with proven knowledge of tool-calling and reasoning agent patterns.
RAG & LLM Engineering: Deep understanding of RAG techniques, prompt engineering, vector databases, embedding models, and fine-tuning methodologies.
Structured & Unstructured Data: Solid background in feature engineering, data transformation, and managing both structured databases and unstructured content streams.
Communication & Mentorship: Exceptional written and verbal communication skills with a proven track record of translating complex AI concepts into executive business narratives and coaching team members.
Preferred Assets & Nice-to-Haves
Hands-on experience with AWS AI/ML services (SageMaker, AWS Bedrock, Lambda).
Familiarity with enterprise data warehousing and big data pipeline tools (AWS Glue ETL, Glue Catalog, Glue Data Quality, and AWS Step Functions).
Summary
If you are a tech-savvy Data Scientist III who pairs 5+ years of core machine learning mastery with hands-on GenAI, agentic AI frameworks (LangChain/LangGraph), PySpark, and RAG architecture skills, this 12-month hybrid contract opportunity is an ideal next step. Bring your analytical curiosity, agentic AI expertise, and technical leadership to our client's team today!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
More about this job
Responsibilities
The Data Scientist III will translate business problems into analytical models, build GenAI applications and AI agents, and write PySpark and SQL queries to integrate large datasets. The role also presents findings to executives and mentors junior data scientists and engineers.
Requirements
Candidates need 5+ years of enterprise machine learning experience, expert Python, strong SQL and PySpark skills, and hands-on experience with LangChain, LangGraph or CrewAI. Strong RAG, vector database and communication skills are also required.
Skills
- Python
- PySpark
- SQL
- LangChain
- LangGraph
- CrewAI
- RAG architecture
- Vector databases
- Embedding models
- Prompt engineering
- Fine-tuning LLMs
- Tool-calling agents
- Multi-agent coordination
- Machine learning
- Supervised learning
- Unsupervised learning
- Predictive modelling
- Feature engineering
- Data transformation
- Structured and unstructured data
- AWS SageMaker
- AWS Bedrock
- AWS Lambda
- AWS Glue ETL
- AWS Glue Data Quality
Categories
- Data & Analytics
- Technology
- Consulting
Keywords
- Data Scientist
- machine learning
- generative AI
- GenAI
- agentic AI
- RAG
- retrieval-augmented generation
- LangChain
- LangGraph
- CrewAI
- Python
- PySpark
- SQL
- vector databases
- embedding models
- prompt engineering
- fine-tuning
- AWS SageMaker
- AWS Bedrock
- AWS Glue
Seniority
Senior
Tools
- Python
- PySpark
- SQL
- LangChain
- LangGraph
- CrewAI
- AWS SageMaker
- AWS Bedrock
- AWS Glue
Languages
- English
Fields of study
- Computer Science
- Statistics
- Mathematics
- Data Science