Data Scientist
Job in
Edmonton, Alberta, Canada
Listing for:
WCB Alberta
Full Time, Seasonal/Temporary
position
Listed on 2026-02-16
Job specializations:
-
IT/Tech
Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
As an equal opportunity employer, we are looking to build a diverse workforce that reflects the diversity of our clients and the customers we serve. Learn more about working for WCB at Careers - WCB Alberta
Job Title:
Data Scientist
Job Type:
Permanent / Full time
Job Location:
Edmonton, Alberta
Data Scientist
Machine Learning Team
Edmonton, Calgary, Alberta
Permanent Full-Time Position
People are at the heart of everything we do.
If you value service, care, excellence, trust and fairness, you’ll fit right in. You'll play an important role in making a difference that creates a safer, healthier and stronger Alberta by putting people first. We work together every day to help minimize the impact of workplace injuries and illnesses on Alberta workers and employers.
As the independent operator and administrator of the province’s Workers’ Compensation Act, WCB-Alberta provides protection for over two million workers and nearly 200,000 Alberta employers. Our employees are inspired to make a positive impact on the lives of injured workers and businesses throughout the province.
Your responsibilities:
Collect and preprocess data from both internal and external sources, curating datasets for machine learning model analysis and training, encompassing data cleansing, integration, transformation, and dimensionality reduction.Establish comprehensive documentation, metadata, standards, and governance protocols concerning data preprocessing techniques and data asset management in the context of machine learning.Deploy scalable machine learning solutions for seamless integration into client-facing applications.Implement rigorous monitoring, maintenance, and reporting protocols for pre-existing models, originating from both internal and external sources.Contribute to the agile and structured evolution of novel machine learning capabilities, encompassing iterative exploration, pilot phases, and proof of concept, preceding their enterprise-wide deployment.Oversee a portfolio of diverse analytics projects, steering them towards delivering comprehensive end-to-end solutions. This involves crafting novel insights, ensuring the robust design and upkeep of data pipelines, and transforming predictive models into prescriptive analytics for optimized business outcomes.Extract pivotal insights and wield influential impact on stakeholders' strategic decision-making and planning. Accomplish this through masterful presentations and data-driven business recommendations.Possess the acumen to engage directly with business stakeholders, skillfully translating their objectives into well-defined analytical problems, thereby bridging the gap between business needs and data-driven solutions.Receive guidance and training from the Team Lead and Machine Learning team, encompassing various methodologies, techniques, tools, and products.Assist fellow data scientists in the development of analytical and predictive models aimed at resolving complex business challenges.Collaborate closely with data science peers to assess machine learning models for AI platforms, calculate performance metrics, and offer data-driven insights.Your experience and skills:
A Bachelor's Degree in a quantitative field such as Statistics, Mathematics, Computer Science, or Engineering, accompanied by a minimum of 1 year of hands-on experience in handling unstructured data.A Master's Degree in a quantitative field like Statistics, Mathematics, Computer Science, or Engineering, with substantial experience dealing with unstructured data sources, will be duly considered.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, and a broad knowledge of ML models, including linear regression, tree-based regression/classification, clustering, and factor analysis, is essential.Expertise with natural language processing and large language model is required.Strong interpersonal, leadership, and communication skills, including the…
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