Senior Data Scientist
Toronto, ON · On-site +1
... credit scoring models) for lending business. * Conduct in-depth data analysis and feature ... Validate, back-test, and monitor existing credit risk models to ensure predictive accuracy and ...
Senior Data Scientist
Toronto, ON · On-site +1
... credit scoring models) for lending business. * Conduct in-depth data analysis and feature ... Validate, back-test, and monitor existing credit risk models to ensure predictive accuracy and ...
Head of AI Safety
Toronto, ON · Remote
This is a remote position. Candidates must be based in Ontario, Canada, due to employment and ... test scenarios, model responses, scoring criteria, safety policies, and evaluation results.
Head of AI Safety
Toronto, ON · Remote
This is a remote position. Candidates must be based in Ontario, Canada, due to employment and ... test scenarios, model responses, scoring criteria, safety policies, and evaluation results.
... test results into business context. * You have experience with funnel and cohort analysis ... Working knowledge of segmentation models, propensity scoring, churn prediction, or LTV modeling ...
Quick apply
... test results into business context. * You have experience with funnel and cohort analysis ... Working knowledge of segmentation models, propensity scoring, churn prediction, or LTV modeling ...
We are open to remote candidates across Canada - you will be required to work on EST hours. Who we ... You're excited by the chance to help define how BIMM builds, tests, and ships agentic software for ...
Quick apply
We are open to remote candidates across Canada - you will be required to work on EST hours. Who we ... You're excited by the chance to help define how BIMM builds, tests, and ships agentic software for ...
Senior AI Engineer, IT Solutions 1
Toronto, ON · On-site +1
CA$98K - CA$164K/yr
Req ID: 137430 Remote Position: Hybrid Region: Americas Country: Canada State/Province: Ontario ... Develop, test, and refine AI prompts and orchestration workflows using frameworks like LangChain ...
Senior AI Engineer, IT Solutions 1
Toronto, ON · On-site +1
CA$98K - CA$164K/yr
Req ID: 137430 Remote Position: Hybrid Region: Americas Country: Canada State/Province: Ontario ... Develop, test, and refine AI prompts and orchestration workflows using frameworks like LangChain ...
This role is a full-time and fully remote opportunity! We're looking for a Product Manager who ... Control UI The supervisor and admin console - scorecard configuration, routing, live monitoring, QA ...
This role is a full-time and fully remote opportunity! We're looking for a Product Manager who ... Control UI The supervisor and admin console - scorecard configuration, routing, live monitoring, QA ...
Remote Test Scoring information
See Ontario salary details
$13.88 is the 25th percentile. Wages below this are outliers.
$10.58 - $15.87
40% of jobs
The median wage is $17.44 / hr.
$15.87 - $21.15
34% of jobs
$24.46 is the 75th percentile. Wages above this are outliers.
$21.15 - $26.44
2% of jobs
$26.44 - $31.73
2% of jobs
$31.73 - $37.02
3% of jobs
$37.02 - $42.31
4% of jobs
$42.31 - $47.60
5% of jobs
$47.60 - $52.88
3% of jobs
$52.88 - $58.17
3% of jobs
$58.17 - $63.46
1% of jobs
$63.46 - $68.75
2% of jobs
$10
$27
$68
How much do remote test scoring jobs pay per hour?
As of Sep 4, 2026, the average hourly pay for remote test scoring in Ontario is $27.32, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $37.26 per hour, depending on experience, location, and employer.
What is a remote test scoring?
A Remote Test Scoring job involves evaluating and grading standardized test responses, essays, or assessments from students, typically based on a set of guidelines or a scoring rubric. These jobs are usually seasonal and may require a background in education or a specific subject. Scorers work from home using a computer and internet connection, following strict accuracy and consistency standards. Training is often provided before scoring begins.
What skills and qualifications are needed for remote test scoring?
To thrive as a Remote Test Scorer, you need strong analytical skills, attention to detail, and a solid understanding of assessment rubrics, often supported by a bachelor’s degree or relevant teaching experience. Familiarity with online scoring platforms and secure data management systems is commonly required. Excellent time management, self-motivation, and clear written communication help candidates excel in this independent, deadline-driven role. These skills ensure fair, accurate, and efficient evaluation of student assessments from a remote environment.
What does a typical workday look like for a remote test scorer?
A typical workday as a Remote Test Scorer involves logging onto a secure online scoring platform, reading and evaluating student assessments according to specific rubrics and guidelines, and entering scores and feedback electronically. Most positions offer flexible scheduling, but scorers are generally expected to meet daily or weekly quotas. It’s common to work independently, but you may have access to support from team leaders or participate in virtual training and calibration sessions. Attention to detail and maintaining focus for extended periods are crucial, as the accuracy and consistency of scoring directly impact students’ results.
What are popular job titles related to Remote Test Scoring jobs in Ontario?
For Remote Test Scoring jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Remote Test Scoring jobs in Ontario look for?
The top searched job categories for Remote Test Scoring jobs in Ontario are:
Full-time
This job post has expired today. Applications are no longer accepted.
Job description
Role Overview
As a Senior Credit Risk Modeling – Data Science, you will be an individual contributor responsible for developing, validating, and maintaining predictive credit risk models for our unsecured personal lending products. You will work closely with data science, risk, and business teams to optimize risk strategies and enhance the overall credit decisioning framework.
Key Responsibilities
- Lead the development of credit risk predictive models (e.g., PD, LGD, EAD, propensity to default, credit scoring models) for lending business.
- Conduct in-depth data analysis and feature engineering using internal and external data sources to improve model performance.
- Validate, back-test, and monitor existing credit risk models to ensure predictive accuracy and regulatory compliance.
- Partner with business and operations teams to integrate model outputs into lending strategies and decisioning processes.
- Develop and maintain documentation for model development, validation, and governance purposes in line with regulatory expectations.
- Provide insights on portfolio risk trends, early warning indicators, and potential loss drivers.
- Mentor junior analysts and contribute to building a strong modeling and analytical culture within the team.
Required Qualifications & Experience
- Bachelor’s or Master’s degree in Statistics, Mathematics, Economics, Data Science, or a related quantitative field.
- 8–10years of experience in credit risk modeling within a lending environment.
- Strong expertise in statistical modeling, machine learning, and predictive analytics (e.g., logistic regression, decision trees, gradient boosting, neural networks).
- Proficiency in programming languages such as Python, R, or SAS; SQL experience essential.
- Solid understanding of credit risk concepts, portfolio management, and lending business processes.
- Excellent problem-solving, communication, and stakeholder management skills. Preferred Skills
Preferred
- Experience with cloud-based data platforms or modern analytics tools.
- Familiarity with alternative data usage in credit risk models.
- Exposure to model governance and audit processes in regulated financial institutions.
- Experience with model validation frameworks and regulatory compliance requirements in Canada (OSFI) or equivalent international standards.
What We Offer
- Competitive base salary + performance bonus + equity package.
- Fast-growth startup environment with direct impact on product and P&L.
- Flexible work model (hybrid/remote options).
- Learning budget, health benefits, and team culture focused on data and innovation.