Data Scientist or Decision Scientist
$110,000–$140,000 year
HybridRichmond Hill, Ontario, Canada
Job Summary
Apply machine learning, predictive modeling, and statistical analysis to develop solutions driving success in multifamily real estate. Design, build, and deploy AI agents and multi-agent workflows on AWS infrastructure, taking use cases from prototype through production. Validate scientific methodologies and project outcomes while collaborating to enhance rental pricing optimization, demand forecasting, and property management efficiency. Contribute to the company's large language model and agentic AI strategy, leveraging retrieval-augmented generation to extract insights from unstructured data and automate workflows. Use statistical methods to transform large datasets into actionable insights supporting data-driven decisions across occupancy, tenant behavior, and operational efficiency. Work with cross-functional teams to promote a data-first, AI-first culture throughout the organization.
Required Qualifications
- 5+ years of relevant experience in predictive modeling, machine learning, and advanced statistics to solve business problems
- Proficiency in Python
- Intermediate to expert-level understanding of machine learning techniques, including gradient-boosted trees, clustering, neural networks, deep learning, and transformer architectures
- sound judgment on when to apply classical ML vs LLM-based approaches
- Work Authorization Requirement: Applicants must be legally authorized to work in Canada at the time of application and throughout employment
- The company does not provide visa sponsorship for this role
Desired Qualifications
- A PhD or Master in a quantitative discipline such as mathematics, science, engineering, statistics, AI, computer science, or a related field
- candidates with a Bachelor's degree with relevant experience
- experience using any tools such as scikit-learn, XGBoost, PyTorch, LightGBM, pandas, and numpy
- Hands-on experience building LLM-powered applications: prompt engineering, RAG pipelines, embeddings/vector search, and LLM evaluation
- Experience with agentic frameworks (e.g., Strands Agents, LangGraph, LangChain)
- Curiosity, ownership, and a bias toward shipping production-ready solutions - comfortable working in ambiguous, fast-moving problem spaces
- Excellent communication, time management, and organizational skills
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