Data Scientist III
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Must have
- 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.
Full description
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. Domain expertise in industrial contexts such as processing and mining is a significant advantage. Strong communication skills are essential to effectively share insights, educate stakeholders, and demonstrate the value of developed solutions.
Don't miss out on this outstanding opportunity to be part of one of Canada's leading mining companies and join our team!
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).