Data Scientist III
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Key skills for this role
About the Role
Teck Resources is looking for a Data Scientist III to work on end-to-end data science projects, from exploration to deployment, with a focus on industrial applications in mining and processing.
Key Skills for This Role
Responsibilities
- Design, develop, and deploy machine learning models, advanced analytics, and Generative AI solutions in production environments
- Implement and maintain robust workflows, including experiment tracking, model versioning, performance evaluation, monitoring, drift detection, and retraining strategies
- Collaborate with cross functional teams to understand business challenges and translate them into data driven solutions
- Collect, process, and analyze large scale datasets from diverse sources using modern data engineering practices
- Ensure scalability, reliability, and security of data pipelines and deployed models
- Communicate findings clearly to technical and non technical stakeholders
- Continuously evaluate and improve models based on feedback and evolving business needs
- Stay current with emerging technologies and best practices in data science, machine learning, and industrial analytics
Requirements
- Master’s or PhD in Data Science, Computer Science, Statistics, or a related quantitative field
- 5+ years of experience in data science, with proven expertise in machine learning and statistical modeling
- Hands on experience in productionizing ML solutions and implementing MLOps practices
- Strong programming skills in Python and proficiency with ML frameworks (Scikit learn)
- Experience with cloud platforms (e.g., Microsoft Azure), Databricks, and containerization (Docker)
- Solid understanding of data development principles and distributed systems
- Excellent communication and presentation skills
Full Job Posting
Role Overview
- Reporting to the Lead, Data Scientist, the Data Scientist who joins the team is someone who excels in statistical modeling, machine learning, and AI, while also possessing strong capabilities in productionizing solutions and implementing mature workflows.
- The successful candidate will work on end to end data science projects, from data exploration and model development to deployment and monitoring in production environments.
Key Responsibilities
- Be a courageous safety leader, adhere to and sponsor safety and environmental rules and procedures.
- Design, develop, and deploy machine learning models, advanced analytics, and Generative AI solutions in production environments.
- Implement and maintain robust workflows, including experiment tracking, model versioning and performance evaluation, production model monitoring, drift detection, and retraining strategies.
- Collaborate with cross functional teams to understand business challenges and translate them into data driven solutions.
- Collect, process, and analyze large scale datasets from diverse sources using modern data engineering practices.
- Ensure scalability, reliability, and security of data pipelines and deployed models.
- Communicate findings clearly to technical and non technical stakeholders, emphasizing model interpretability, actionable insights, and a clear understanding of the key drivers behind model behavior.
- Continuously evaluate and improve models based on feedback and evolving business needs.
- Stay current with emerging technologies and best practices in data science, machine learning, and industrial analytics.
Qualifications
- Master’s or PhD in Data Science, Computer Science, Statistics, or a related quantitative field, with strong practical experience in applying Data Science techniques to real world problem settings.
- 5+ years of experience in data science, with proven expertise in machine learning and statistical modeling. Experience with causal inference or causal modeling approaches is a plus.
- Hands on experience in productionizing ML solutions and implementing MLOps practices (e.g., CI/CD for ML, model monitoring, experiment tracking).
- Strong programming skills in Python and proficiency with ML frameworks (Scikit learn).
- Experience with cloud platforms (e.g. Microsoft Azure), modern analytics platforms such as Databricks, and containerization (Docker).
- Solid understanding of data development principles and distributed systems.
- Familiarity with industrial domains such as processing and mining is highly desirable.
- Excellent communication and presentation skills to convey technical concepts to diverse audiences.
- Ability to work collaboratively in agile teams and adapt to fast paced environments.
- Passion for innovation, continuous improvement, and a strong focus on delivering tangible value through data driven solutions.
Pay Range
- CAD 107,000 CAD 132,000 per year.
Workplace Type
- Hybrid
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