Data Scientist building AI fraud detection models for Oscilar’s risk platform. Analyzing large datasets and strengthening fraud prevention for banks, fintechs, and digital organizations.
About the role
- Data Scientist on the Machine Learning Team for Alberta’s Workers’ Compensation Board. Developing scalable machine learning solutions and overseeing analytics projects to improve workplace safety.
Responsibilities
- Collect and preprocess data from both internal and external sources, curating datasets for machine learning model analysis and training
- Establish comprehensive documentation, metadata, standards, and governance protocols concerning data preprocessing techniques and data asset management
- Deploy scalable machine learning solutions for seamless integration into client-facing applications
- Implement rigorous monitoring, maintenance, and reporting protocols for pre-existing models
- Contribute to the agile and structured evolution of novel machine learning capabilities
- Oversee a portfolio of diverse analytics projects, steering them towards delivering comprehensive end-to-end solutions
- Extract pivotal insights and wield impactful influence on stakeholders' strategic decision-making and planning
Requirements
- A Bachelor's Degree in a quantitative field such as Statistics, Mathematics, Computer Science, or Engineering
- A minimum of 1 year of hands-on experience in handling unstructured data
- Familiarity with machine learning concepts and applied research in a related field
- Proficiency in a machine learning programming language (Python) is mandatory
- Strong SQL skills are a fundamental requirement
- Extensive experience in data preparation techniques, including data cleansing, wrangling, feature engineering
- A broad knowledge of ML models, including linear regression, tree-based regression/classification, clustering, and factor analysis
- Expertise with natural language processing and large language model is required
- Strong interpersonal, leadership, and communication skills
- Exceptional written and presentation skills are a mandatory requirement
- Experience with processing modeling, data modeling and governance/process documentation
- Project management experience is an asset.
Benefits
- Flexible work schedules
- Hybrid work opportunities (combination of work from physical office and primary home residence)
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