Data ScientistTeranet • Toronto C6A, ON, Canada

Data Scientist

Teranet • Toronto C6A, ON, Canada

30+ days ago

Job type

Full-time

Job description

## 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

## 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

## 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.

## Background in

applied econometrics

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.## Experience in

spatial data science

real estate valuation models

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Data Scientist • Toronto C6A, ON, Canada

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