Senior Data Scientist (Machine Learning & Generative AI)

Bring your passion for data, machine learning, and GenAI to the insurance sector for our client. Help transform complex business problems into practical, cutting-edge solutions while contributing to advanced analytics initiatives that create value across Canadian business units.

What is in it for you:

- Salaried: $65-75 per hour.
- Incorporated Business Rate: $77-87 per hour.
- 12-month contract providing coverage for maternity leave.
- Full-time position: 37.50 hours per week.
- Hybrid work arrangement with 3 days on-site, including Thursdays.

Responsibilities:

- Data Science and Machine Learning
- Translate business goals into analytical problems and identify optimal algorithms, statistical techniques, and/or GenAI architecture suitable for the business problem at hand.
- Work in cross-functional teams to develop ML/data science products, including GenAI applications.
- Apply best-in-breed 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
- Design, develop, and deploy GenAI solutions, including AI agents, chatbots, and autonomous systems that solve complex business problems.
- Research and pilot the latest GenAI technologies, RAG (Retrieval-Augmented Generation) techniques, and agentic frameworks such as LangChain, LangGraph, and CrewAI.
- Implement AI bots/agents with advanced reasoning capabilities and tool-use patterns.




- Work with vector databases and embedding models to build intelligent information retrieval systems.
- Technical Leadership & Collaboration
- Break down broader data science development milestones into actionable goals, activities, and work plans.
- Create and maintain technical design artifacts describing application functionality, data models, interfaces, and integrations.
- Engage and negotiate with stakeholders, make business recommendations, and effectively present findings to multiple levels of stakeholders.
- Champion continuous improvement and foster 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.
- 5+ years of experience developing and implementing data science techniques.
- 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.
- Hands-on expertise with GenAI frameworks and LLM APIs, including experience developing AI bots and agents with reasoning and tool-use capabilities.
- Strong 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.
- Soft skills
- Exceptional communication skills with technical and non-technical stakeholders.
- Effective and concise oral and written storytelling and insights communication skills.
- An ability to manage multiple projects, changing deadlines, and priorities.
- An ability to mentor and guide junior data scientists and data engineers.
- Strong problem-solving and analytical skills.
- Keen attention to detail.
- Fierce curiosity for discovering and leveraging new data.
- An inquisitive mind.
- A willingness to ask questions to help lead projects to commercial value.
- 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.

📌 Senior Data Scientist (Canada)
🏢 BlackCube Labs
📍 Canada