Intermediate Data Scientist
3 weeks ago
6 month contract
Hybrid 5x per month - Toronto
Pay range:
$40-50/hr
Overview:
We are looking for a detail-oriented and driven Intermediate Data Scientist to join our team. In this role, you will be responsible for analyzing large datasets, building AI/ML models, and extracting insights to support fraud detection and anti-money laundering (AML) efforts. You will spend a significant portion of your time working with data, manipulating it, and summarizing analysis to present results in an accessible manner to both technical and business stakeholders.
Responsibilities:
- Spend 50%-70% of your time working with large datasets to extract, manipulate, and clean data for model development.
- Develop and validate AI/ML models, focusing on fraud detection and AML, using Python, SAS, and SQL.
- Conduct in-depth data analysis, summarizing findings and generating insights that can be easily communicated to both technical and business audiences.
- Work closely with cross-functional teams to integrate models and provide continuous monitoring and validation.
- Measure and assess the performance of models, applying statistical and probability-based techniques.
- Focus on identifying behavioral patterns in transactional data, such as credit card statements and balances, to build models that detect fraud or money laundering.
- Ensure that models are built, tested, and validated according to industry best practices.
Must-Haves:
- 3-5 years of experience with Python and SQL.
- 2+ years of experience developing AI/ML models.
- Proficiency in end-to-end model development and validation.
- Strong ability to manipulate and analyze large datasets to extract meaningful insights.
- Experience with fraud detection and AML models, particularly involving transaction and behavioral data.
- Strong presentation and communication skills to summarize and present complex analyses to both technical and business stakeholders.
Nice to Have:
- Experience with SAS for model development and validation.
- Knowledge of risk and market risk, particularly in the context of financial services.
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