Data Scientist I – GenAI & Machine Learning

Recruit Action inc.; Toronto; Hybrid; CAD 95,000 - 110,000; Full time

Job summary

Recruit Action inc. in Toronto, Ontario seeks a Data Scientist I focusing on GenAI and ML to translate business goals into analytical initiatives and to build practical analytics solutions across Canadian units.

This 12-month maternity-cover contract offers hybrid work with 3 days on-site, compensation hourly at $45–50 (salary equivalent $95k–$110k per year) or incorporated rate $55–$60, and a collaborative analytics environment.

Qualifications

• Bachelor’s degree in CS, Statistics, Mathematics, or related field.
• 0–3 years of relevant experience.
• Python for data science and GenAI development.
• SQL and PySpark to extract and integrate data from multiple sources.
• Machine learning for supervised and unsupervised models.
• Data transformation and manipulation of structured and unstructured data.
• APIs, microservices architecture, and cloud-native development.
• GenAI frameworks and LLM APIs for developing AI bots and agents.
• Retrieval-Augmented Generation, prompt engineering, and vector databases/embeddings.
• Chatbot development concepts and conversational AI design.
• Reliability Clearance required.

Responsibilities

• Translate business goals into analytical problems and select suitable algorithms and GenAI architecture.
• Support cross-functional teams in developing ML/data science products and GenAI apps.
• Apply data science methods from design to implementation (descriptive, predictive, ML).
• Focus on feature engineering, model training/evaluation, and prompt engineering for LLMs.
• Design, develop, and deploy GenAI solutions including agents and chatbots.
• Research GenAI tech, RAG, and frameworks like LangChain/CrewAI.
• Assist with AI bots/agents that reason and use tools.
• Work with vector databases and embeddings for intelligent retrieval.
• Create and maintain design artifacts for functionality, data models, interfaces, and integrations.
• Contribute to continuous improvement within analytics community.

Skills

Python

SQL

PySpark

Machine learning

Data wrangling

APIs & microservices

GenAI frameworks

LLM APIs

Prompt engineering

Vector databases

Chatbot development

Cloud-native development

Education

Bachelor's degree in Computer Science, Statistics, Mathematics, or related field

Tools

AWS SageMaker

LangChain

LangGraph

CrewAI

AWS Glue

SageMaker

LLM APIs

Job description

Data Scientist I – GenAI & Machine Learning

Bring your passion for data, machine learning, and GenAI to the insurance sector for our client. Support the development of practical, innovative solutions while contributing to advanced analytics initiatives across Canadian business units.

What is in it for you

• Salaried: $45-50 per hour.
• Incorporated Business Rate: $55-60 per hour.
• 12-month contract providing coverage for maternity leave.
• Hybrid work arrangement with 3 days on-site, including Thursdays.

Responsibilities

Data Science and Machine Learning

• Support the translation of business goals into analytical problems and the identification of suitable algorithms, statistical techniques, and/or GenAI architecture.
• Support cross-functional teams in developing ML/data science products, including GenAI applications.
• Support the application of data science techniques, including descriptive, predictive, and machine learning methods, from design to implementation.
• Focus on feature engineering, model training, model evaluation, and prompt engineering for LLMs.

GenAI & Agentic AI Development

• Support the design, development, and deployment of GenAI solutions, including AI agents, chatbots, and autonomous systems.
• Support research and pilots involving GenAI technologies, RAG (Retrieval-Augmented Generation) techniques, and agentic frameworks such as LangChain, LangGraph, and CrewAI.
• Support the implementation of AI bots/agents with reasoning capabilities and tool-use patterns.
• Work with vector databases and embedding models to build intelligent information retrieval systems.

Technical Execution & Collaboration

• Support senior team members in completing data science development activities and work plans.
• Create and maintain technical design artifacts describing application functionality, data models, interfaces, and integrations.
• Work within a narrower project scope, typically one project at a time.
• Work with limited to no direct stakeholder interaction.
• Contribute to continuous improvement and innovation within the analytics community.

What you will need to succeed

Required qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field, or equivalent experience.
• Open to recent graduates and candidates with 0-3 years of relevant experience.
• Proficiency in Python for data science and GenAI application development.
• Experience writing complex SQL and PySpark queries to extract and integrate data from multiple database sources.
• Proficiency in machine learning, including supervised and unsupervised models.
• Demonstrated experience in data transformation, data manipulation, and working with structured and unstructured data.
• Strong understanding of APIs, microservices architecture, and cloud-native development.
• Experience with GenAI frameworks and LLM APIs, including developing AI bots and agents with reasoning and tool-use capabilities.
• Understanding of Retrieval-Augmented Generation techniques, prompt engineering, and fine-tuning methodologies, with familiarity with vector databases and embedding models.
• Experience with chatbot development concepts and conversational AI design.
• Reliability Clearance required.

Preferred qualifications

• Experience with AWS services, including SageMaker, Lambda, Bedrock, and other AI and machine learning services.
• Experience with data warehousing, pipelines, and big data technologies such as AWS Glue for ETL, Glue Catalog, Glue Data Quality, and AWS Step Functions.
• Exceptional communication skills.
• Effective and concise oral and written storytelling and insights communication skills.
• Strong problem-solving and analytical skills.
• Keen attention to detail.
• Fierce curiosity for discovering and leveraging new data.
• A willingness to ask questions.
• A willingness to recognize that innovation attempts can lead to failure.
• A passion for solving problems.
• A focus on efficient execution and delivery.
• A thirst for continuously updating data science knowledge.