Overview
Data Scientist (AI & Data Engineering) Jobs in Toronto, Ontario, Canada at Hays
Title: Data Scientist (AI & Data Engineering)
Company: Hays
Location: Toronto, Ontario, Canada
Role: Data Scientist (AI & Data Engineering)
Length: 1 year contract (strong likelihood of extension)
Location: Downtown Toronto (4 days onsite)
Hourly Rate: 60-80/hour
Your New Company
Our client is a leading global institutional investor with a strong focus on long-term value creation through data-driven decision making. With a mature data ecosystem and ongoing investment in modern platforms like Microsoft Fabric, the organization is building advanced capabilities to leverage both internal enterprise data and external market intelligence to drive strategic insights across its portfolio.
Your New Role
As a Data Scientist (AI + Data Engineering), you will play a critical role in unlocking the power of external market data by integrating it with internal enterprise datasets to generate high-impact insights. Operating across the full data lifecycle—from ingestion and transformation through to modeling and insight delivery—you will build scalable analytical solutions within a Microsoft Fabric environment.
Key responsibilities include:
- Designing and building data pipelines using Microsoft Fabric (Dataflows, Notebooks, Lakehouse, Data Pipelines)
- Integrating external datasets (e.g., market, macro, and demographic data from vendors such as CBRE, JLL, CoStar) with internal systems (e.g., asset management and investment platforms)
- Implementing Medallion architecture (Bronze, Silver, Gold layers) to enable governed, reusable datasets
- Developing predictive and statistical models to identify trends, forecast outcomes, and detect anomalies
- Performing advanced analytics including time-series modeling, multivariate analysis, and scenario modeling
- Creating insight-ready datasets to support Power BI reporting, AI-driven use cases, and decision support applications
- Contributing to ML lifecycle management, including model training, tuning, deployment, and monitoring within production pipelines
- Ensuring data quality, governance, and model explainability across all outputs
- Collaborating with data engineers, delivery leads, and business stakeholders to translate business problems into actionable insights
What You’ll Need to Succeed
To succeed in this role, you will bring a strong blend of data science expertise and hands-on data engineering capability:
- 5–8+ years of experience in Data Science, Machine Learning, or Advanced Analytics
- Proficiency in Python (pandas, PySpark, ML libraries) and SQL
- Proven experience working with large, multi-source datasets and delivering production-grade ML models
- Strong hands-on experience with data transformation, pipeline development, and data modeling concepts
- Experience with Microsoft Fabric or similar modern data platforms (e.g., Azure Data Platform, Databricks)
- Solid understanding of Medallion architecture and best practices in data engineering
- Expertise in statistical modeling and machine learning techniques (regression, classification, clustering, time-series forecasting)
- Ability to translate business problems into analytical frameworks and actionable insights
- Strong communication skills, with the ability to clearly explain findings to non-technical stakeholders
Nice-to-have:
- Experience working with real estate, investment, or market datasets
- Familiarity with external data providers such as CBRE, JLL, CoStar
- Exposure to Azure AI, AI/ML platforms, or LLM-based solutions
- Experience integrating analytics into end-to-end data products or intelligent applications
What You’ll Get in Return
- Opportunity to work on high-impact, enterprise-scale data initiatives combining external market intelligence with internal data assets
- Exposure to a cutting-edge Microsoft Fabric data ecosystem
- A highly collaborative, data-driven environment with strong executive sponsorship for analytics initiatives
- The ability to influence investment strategies and business decision-making through advanced analytics
- Competitive compensation and a flexible hybrid work model in Toronto
What You Need to Do Now
If you’re a Data Scientist who thrives at the intersection of data engineering, advanced analytics, and business impact, apply now or reach out directly for a confidential discussion.
