Data Scientist

Teranet is Canada’s leader in the delivery and transformation of statutory registry services with extensive expertise in land and commercial registries. We also market insightful property and data solutions, as well as practice management automation to thousands of customers in the real estate, financial services, government, utilities, and legal markets.

Connect. Grow. Thrive Together.

To learn more about who we are visit our website:  www.teranet.ca

The Data & Analytics team within the Commercial Solutions line of business has an ambitious mandate, where we are accountable for leveraging Data & Analytics to deliver business value both internally as well as to external clients through the following:

• Enhance existing or create new products and services with proprietary data assets and partnering with external data providers, through the application of data analytics

• Design and deliver custom data solutions to fulfill specific client needs

• Explore and analyze data to generate business insights to enhance decision-making

• Demonstrate thought leadership in the ecosystem in which we operate

• Identify and implement opportunities for operational efficiencies across the organization

In addition, this team will play an important role in evangelizing and educating of the value of Data & Analytics to the rest of the organization, in support of cultivating a data-driven culture.

You will play a key role in our dynamic team, taking accountability for the design, development, implementation, and maintenance of cutting-edge Machine Learning models. As a vital member of the Data Science team, the role involves collaborating closely on Machine Learning (ML) and Artificial Intelligence (AI) product design and development.

The primary focus will be on supporting data products/services and operational efficiency initiatives. This includes a special emphasis on providing tailored products for Financial Solutions business and expanding these capabilities across the organization to address a diverse range of AI needs. Join us in shaping the future of our data-driven initiatives and contributing to innovative solutions that make a meaningful impact.

Reason for Vacancy: Replacement

The Data Scientist is accountable for the entire lifecycle of each assigned ML/AI use case, from gathering business requirements all the way to production and maintenance.

• Engage with stakeholders to understand business requirements and objectives of ML/AI use cases

• Identify and acquire the best data sources available to meet use case objectives. Explore data to build foundational data knowledge in subject domain, in partnership with data owners

• Develop cutting-edge ML models tailored to identified use cases and ensure the accuracy, reliability, and innovation of these models is crucial for making impactful contributions to our data-driven initiatives.

• Collaborate closely with Data and MLOps Engineers, to implement the models in the Big Data Platform, leveraging cloud technologies.

• Present technical analyses in a meaningful and intuitive manner, in accordance with the target audience

• For each use case, thoroughly document the objectives, analysis process, methods, and findings to meet quality standards and production requirements

• Continuously monitor and fine tune model performance by evaluating new or revised data sources, modelling techniques, and tools

• Identify, evaluate, and manage external vendors for specialized skills

• Actively partner with the Data Governance team to ensure that the use of data for each use case complies with Teranet policies and procedures

• Be attuned to the latest developments in Data & Analytics, and share learnings and ideas with team to cultivate a spirit of innovation

• As a team, develop framework to standardize analysis processes, methodologies, and documentation

• Provide feedback and suggestions to enhance and evolve our Analytics program to better meet our corporate goals

• Evangelize the value of Data & Analytics at Teranet through engagement with the rest of the organization

• Delegate data collection, extraction, analysis and/or visualization tasks to more junior members of the team in support of the delivery of the ML/AI use cases

• Provide direction for and review the assigned work

• Provide learning and growth opportunities to support the professional development of other team members

• Is keen to understand the business – data science cannot be done in a vacuum – we need to be close to the business so that we understand what we are trying to solve for and what the data means

• Tells stories from data – data analytics is not data dump – it needs to be meaningful and intuitive to the end user in order to realize the inherent business value

• Challenges the status quo – the state of business and the field of data science are constantly evolving, and we need to as well. Assumptions and old ways of doing things are open season, as long as you bring along workable and relevant solutions articulated in a professional manner.  Proactively pursue and learn about new analytical tools and methodologies to solve problems in new and innovative ways.

• Is good at problem solving – someone who can “connect the dots”, and have a logical and methodical way to tackle new and complex problems

• Takes pride in your work – your work is diligent and thorough and you are proud of your reputation for high-quality and reliable work

• Is a quick study – the successful candidate must be curious, resourceful, and dig into the weeds to ask the right questions and figure things out independently

• Graduate degree in quantitative field (Data Science, Statistics, Economics, Computer Science, Engineering, or related). Equivalent professional experience will be considered.

• 5+ years of proficiency in Python programming language, with a strong emphasis on Machine Learning applications.

• Proven experience building advanced regression and predictive models, including boosting, model stacking, and non-parametric methods.

• Strong foundation in statistical modeling and inference, able to design experiments, assess model assumptions, and apply appropriate statistical techniques to real-world data.

• Practical experience with cloud computing environments (Azure, AWS, or Google Cloud) and distributed data processing (PySpark).

• Experience with data query languages such as SQL.

• Skills in data visualization tools, such as Tableau, for effective presentation of analytical findings.

• Experience in spatial data science or real estate valuation models

• Background in applied econometrics or advanced statistical analysis

• Expertise in time series forecasting, using traditional and neural network based methods for trend and demand prediction

• Proficiency in deep learning techniques (e.g., feedforward, convolutional, or transformer models) for complex regression and pattern recognition tasks.

Let’s Talk Pay

We believe in being upfront about pay and helping you make informed decisions about your career. The annual pay range for this role is $125,000-$137,500 CAD, inclusive of base salary and target incentive pay. We understand that great talent comes in many forms, each with unique skills, experience, and potential. Your salary will be tailored to reflect the experience you bring and the impact you’re ready to have on this role.

At Teranet, we also know that compensation extends far beyond a pay cheque. Along with your cash compensation, we offer a comprehensive package which includes the following:

• 100% Employer Paid Health Benefit Plan

• Employer Matching Retirement Savings Plan

• Paid Vacation, Floater Days & Sick Leaves

• Maternity, Parental and/or Adoption Leave Top-Up Programs

• Corporate Discounts & GoodLife Group Rate Membership

• Employee Assistance Program – for you and your loved ones!

Our Human Approach to Hiring

At Teranet, we use smart technology to make hiring faster and more efficient. Artificial Intelligence (AI) tools help us review applications and identify strong matches—but the real decisions? Those are made by our awesome people.

Every interaction you’ll have, and every decision we make, is led by humans. AI may support us, but it’s human connection that drives every hire.