Educational requirements: Bachelor
English requirements: Competent English
Requirements for skilled employment experience for years: 5-8 years
Required residence status: Temporary visa, Permanent resident, Citizen
Accept remote work: unacceptable
About the Opportunity
We are looking for experienced data scientists to work on a range of projects for our clients.
You'll need to have at least three to five years' corporate experience in data science roles. The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and the ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.
The role is suitable for a highly creative Data Scientist with hands-on experience building and enhancing statistical, quantitative, or machine learning models on an end-to-end project. You will be well-developed in analytical knowledge across data mining, data modeling, data transformation, and data visualization.
Responsibilities
Analyze raw data: data cleansing and data structuring for downstream processing Design and build statistical predictive models and machine learning algorithm Collaborate with the data engineering team to productionise the model Generate actionable and predictive descriptive insights that drive business value
Qualifications
At least 3 to 5 years of experience in quantitative analytics within the corporate sector A relevant degree in a quantitative field (Actuarial Studies, Statistics, Mathematics, etc) Deep understanding of predictive modeling and machine-learning algorithms (GLM, Decision Trees, Clustering, Random Forest, GBM, etc) Experience in other mathematics focus areas such as optimization, time-series forecasting, next-best-action, or personalization High business acumen to interpret complex technical data and present results to business stakeholders Fluency in R coding Proficiency in SQL within data warehouse ecosystem (Hadoop, Oracle, SQL Server, Teradata, etc) Familiarity with cloud environments such as Azure ML or AWS SageMaker is an advantage
