Data Scientist, Fraud Predictive Analytics
at Dataroles
Toronto, hybrid, mid, full time, CAD 80,000–1,75,000 / year, 5–7 years
posted 02 Nov 2026 · closes 29 Nov 2026
- H2O
- PySpark
- Optimization Algorithms
- Artificial Intelligence
- SparkML
- Machine Learning
- Forecasting
- Multivariate Testing
- Deep Learning
- Quantitative Analytics
- SQL
- XGBoost
- Statistical Analysis
- Python
- Predictive Analytics
About the role
Data Science work from LinkedIn, X, Reddit and Upwork, in one list. Find me work ×
dataroles
What you would do
* Build and refine fraud models that support detection, investigation and prevention across financial crimes work * Gather data from internal owners and outside vendors, then prepare it at useful levels of detail for analysis * Test business hypotheses with statistical and machine learning methods, using patterns in large datasets to shape solutions * Track model and system performance, diagnose problems and improve analytical tools and their efficiency * Explain analytical findings to business partners, turning results into practical recommendations and training
What they are looking for
* You bring five to seven years of work in data science and analytics, with a related degree or equivalent experience * You have built fraud models for a large financial institution, covering investigation, detection or prevention * You bring strong statistical and predictive analytics skills, plus programming experience in SQL, Python or PySpark and machine learning methods
Who this fits
This Toronto-based hybrid role suits a mid-level data scientist focused on fraud analytics. The work combines hands-on modeling and data preparation with communication and collaboration across stakeholders.
From the employer
* Typically between 5 - 7 years of relevant experience in Data Science & Analytics and post-secondary degree in related field of study or an equivalent combination of education and experience. * Advanced degree in Computer Science, Mathematics, Physics, Engineering, Statistics, or other quantitative disciplines and/or equivalent experience * Experience with programming languages (e.g. SQL, Python, PySpark) and machine learning /deep learning algorithms/packages (e.g. XGBoost, H2O, SparkML). * Deep proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms. * Experience building fraud models (investigation, detection, prevention) for a large Financial Institution
What comes with it
Read from dataroles.co, last seen 3d ago.