- Company Name
- Teck Resources Limited
- Job Title
- Data Scientist III
- Job Description
-
**Job Title**
Data Scientist III
**Role Summary**
Lead end‑to‑end data science projects within a mining and processing context. Build, deploy, and monitor machine‑learning models, maintain MLOps pipelines, and translate business challenges into actionable insights. Interface across functions to communicate model value and ensure scalable, secure data solutions.
**Expectations**
- Deliver production‑ready machine‑learning models and advanced analytics within enterprise environments.
- Own full MLOps lifecycle: experiment tracking, version control, CI/CD, performance monitoring, and continuous improvement.
- Operate with industrial datasets (processing and mining) and modern data‑engineering practices.
- Communicate findings to technical and non‑technical stakeholders, educate teams on model mechanics, and advocate data‑driven decisions.
- Uphold safety, security, and environmental policies, acting as a safety leader within data‑science initiatives.
**Key Responsibilities**
1. Design, prototype, and deploy machine‑learning models using Python and frameworks such as Scikit‑learn.
2. Implement, document, and maintain MLOps workflows; manage experiment tracking, model versioning, CI/CD pipelines, and monitoring.
3. Analyze large, heterogeneous datasets, ensuring data quality, scalability, and security across pipelines.
4. Collaborate with cross‑functional teams to translate business problems into data‑science solutions.
5. Provide clear, actionable insights and training to stakeholders, ensuring adoption of developed models.
6. Continuously evaluate model performance, incorporate feedback, and refactor models to meet evolving needs.
7. Stay current with emerging technologies, best practices, and industry trends in data science, MLOps, and industrial analytics.
**Required Skills**
- Advanced programming in Python; expertise in Scikit‑learn or equivalent ML libraries.
- Hands‑on experience launching models in production; proficiency with experiment tracking, model versioning, CI/CD, and monitoring tools.
- Cloud platform proficiency (Microsoft Azure) and containerization (Docker).
- Solid foundation in data‑engineering concepts, distributed systems, and scalable pipeline design.
- Strong statistical and machine‑learning acumen, capable of end‑to‑end solution development.
- Effective communication and presentation skills for diverse audiences.
- Ability to thrive in agile, fast‑paced environments and collaborate across teams.
- Knowledge of safety and environmental standards relevant to mining operations.
**Required Education & Certifications**
- Master’s or PhD in Data Science, Computer Science, Statistics, or a related quantitative discipline.
- 5+ years of professional experience in data science, with demonstrated success in machine‑learning and statistical modeling.
- Certifications in cloud (e.g., Microsoft Azure) and/or MLOps tools are an advantage.