Data Scientist Salary in Saint John, New Brunswick
$41K
20% Low Band Avg
CAD $59K
Average
$77K
80% High Band Avg
Salaries based on experience level
The Average Entry Level salary of Data Scientist in Saint John, New Brunswick is CAD $44K/yr, this salary increases 33% to $59K/yr when reach Mid Level Career.
From Mid to Senior Level the average salary increases 30% from $59K/yr to $77K/yr.
Salary Compared to Canada National Average Salary
- Data Scientist in Saint John, New Brunswick Salary
- vs
- Data Scientist in Canada Salary
The Average Salary of Data Scientist in Saint John, New Brunswick is $59K/yr. This is -22% lower ($-17,259) compared to Canada national average salary of $76K/yr.
Salary Compared to Saint John City Average Salary
- Data Scientist in Saint John, New Brunswick Salary
- vs
- Saint John, New Brunswick City Average Salary
The Average Salary of Data Scientist in Saint John, New Brunswick is +9% higher (5,284) than the average salary for the city of Saint John, New Brunswick $54K/yr.
Data Scientist job description
Job Title: Data Scientist
Overview/Summary of the Role:
A Data Scientist is responsible for analyzing and interpreting complex data sets in order to extract valuable insights that can be used to improve business operations and decision-making. They use a range of statistical and analytical tools to organize and analyze data, and they must be able to communicate their findings to non-technical stakeholders.
Responsibilities and Duties:
- Develop and implement statistical models and algorithms to analyze complex data sets
- Collect and clean data, and ensure data quality and integrity
- Develop data visualizations and dashboards to communicate insights to stakeholders
- Identify trends and patterns in data to inform business decisions
Data Scientist interview questions
Interviewer: Hi, thank you for coming in today. Can you start by telling me about your previous experience in data analysis or data science?
Candidate: Yes, of course. I have worked as a data analyst for the past three years in two different companies. In my previous role, I was also involved in data science projects, where I utilized statistical methods and machine learning algorithms to solve business problems.
Interviewer: Can you give an example of how you have utilized machine learning techniques in your previous work?
Candidate: Sure, in my previous job, we were tasked with predicting customer churn in a telecommunications company. I used logistic regression, decision trees, and gradient boosting techniques to build predictive models. We were able to successfully identify key features that were driving customer attrition and were able to reduce their churn rate by implementing some of our recommendations.
Interviewer: Can you describe a time when you had to collaborate with other departments or stakeholders to solve a problem with data?
Candidate: Yes, in a previous role, I was working with the marketing team to optimize a marketing campaign. I had to collaborate with them to understand their requirements and also gather the necessary data sources. We worked together to develop a data-driven approach to optimize the campaign, which resulted in a 20% increase in conversion rate.