Data Scientist or Decision Scientist

Venterra Realty•Richmond Hill, ON

1d•$110,000 - $140,000•Hybrid

About The Position

Technology is in the DNA of its founders. The Chairman and Co-Founder holds an Engineering Degree and a Master's Degree in Artificial Intelligence. Earlier in their careers, the Chairman and the CEO jointly led the growth and sale of a highly successful software business focused on logistics optimization, subsequently applying their business and technology acumen to the real estate industry, creating Venterra. As a result, the organization is one of the few in the industry with its own in-house property management stack (full spectrum of applications covering rent management, pricing optimization, purchasing, utility billing, work order, and capital expenditure management, etc.), resulting in greater control over its technology destiny. The organization views this capability as a crucial competitive advantage to compete at the highest level of the industry. Venterra has an established competence in Decision Science and is investing heavily in AI - including increasing integration of agentic AI solutions in operational workflows. Current projects on AI/ML/LLM solutions have the potential to revolutionize management, customer experience, and decision optimization. We are looking for a Data Scientist or Decision Scientist to join our growing team, adding and augmenting the strength of our current team.

Requirements

A PhD or Master in a quantitative discipline such as mathematics, science, engineering, statistics, AI, computer science, or a related field is strongly preferred. However, candidates with a Bachelor's degree with relevant experience will also be considered.
5+ years of relevant experience in predictive modeling, machine learning, and advanced statistics to solve business problems.
Proficiency in Python, along with 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.
Intermediate to expert-level understanding of machine learning techniques, including gradient-boosted trees, clustering, neural networks, deep learning, and transformer architectures - and sound judgment on whether to apply classical ML vs. LLM-based approaches.
Strong analytical and problem-solving skills, with the ability to translate data into meaningful insights that influence business outcomes.
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.
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.

Nice To Haves

Experience with agentic frameworks (e.g., Strands Agents, LangGraph, LangChain) is a strong asset.

Responsibilities

Apply machine learning, predictive modeling, and statistical analysis to develop innovative solutions that drive success in multifamily real estate.
Design, build, and deploy AI agents and multi-agent workflows (AWS infrastructure), taking use cases from prototype through production.
Validate scientific methodologies and project outcomes from other team members.
Collaborate on developing models that enhance rental pricing optimization, demand forecasting, and property management efficiency.
Contribute to the company's large language model (LLM) and agentic AI strategy, leveraging LLMs and retrieval-augmented generation (RAG) to extract insights from unstructured data, automate workflows, and improve decision-making processes.
Use statistical methods and techniques to transform large datasets into actionable insights, supporting data-driven decisions across areas like occupancy, tenant behavior, and operational efficiency.
Work with cross-functional teams (software engineering, data engineering, DevOps, cybersecurity) to promote and implement a data-first, AI-first culture throughout the organization.