Predictive Analytics Specialist (ID#5549)

Role overview

Predictive analytics and modelling

• Design, develop, deploy, maintain, and support predictive analytics and machine-learning models.
• Model resident renewal and churn, delinquency risk, occupancy and vacancy, leasing pipelines, rental revenue, NOI, budgeting, property maintenance, and supply-chain management.
• Apply statistical modelling and machine learning to identify trends, patterns, risks, and opportunities; build forecasts and improve model accuracy and impact.
• Monitor model performance, data drift, prediction accuracy, and user adoption; turn property, leasing, financial, and operational data into predictive insights.

Data engineering and delivery

• Build and maintain enterprise data pipelines using Azure Data Factory; develop scalable SQL Server structures, data models, and semantic models.
• Build Power BI dashboards and reports and write SQL queries and DAX calculations.
• Support data quality, cleansing, and governance; perform QA and coordinate UAT with business stakeholders.
• Collaborate with IT and business teams through design, development, deployment, and ongoing support; translate findings into business recommendations.

Experience and skills

• At least 3 years in data science, machine learning, predictive analytics, advanced analytics, or a related area.
• Strong hands-on machine-learning and predictive-modelling experience, including delivery of analytics, statistical analysis, data-mining, or data-science solutions.
• Strong Python; experience with large complex datasets, forecasting and model evaluation, SQL, and data modelling.
• Experience with one or more of Pandas, NumPy, Scikit-Learn, XGBoost, TensorFlow, or PyTorch; Microsoft data technologies such as Azure Data Factory, Power BI, Azure Data Lake, or SQL Server are also listed.

Other qualifications

• Strong analytical, problem-solving, attention-to-detail, and communication skills; able to explain technical findings as business recommendations and work independently or collaboratively.
• A related post-secondary diploma or degree is preferred; equivalent professional training and experience may be considered.
• Real estate, property management, or REIT experience is an asset.

Workplace arrangement

• Hybrid arrangement in Downtown Calgary: three days per week onsite and two days remotely.