Data Scientist III

Résumé du poste

Design, develop, and deploy machine learning and Generative AI solutions within production environments. Collaborate with cross-functional teams to translate business challenges into scalable, data-driven solutions and maintain robust MLOps workflows.

Détails du poste

Location: Vancouver, BC, Canada Employment Type: Regular Full Time Workplace Type: Hybrid About Our Vancouver Office Located in the heart of downtown Vancouver, between the Pacific Ocean and the Coast Mountains, Teck’s Corporate Office sits in one of Canada’s most culturally diverse cities. Surrounded by world-renowned nature and globally inspired cuisine, the office brings together many of Teck’s corporate functions - all working toward Teck’s purpose of providing the essential resources the world relies on. 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). 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 - $132,000 per year The actual amount offered is determined based on the successful candidate’s relevant experience, skills, and competencies and considers internal equity. Why Teck At Teck, your work matters—to the world, to our communities and to your future. As a leading Canadian resource company, we focus on responsibly providing the metals essential for global development and the energy transition while caring for the people, communities and land that we love. We do this guided by our values that, together, form The Teck Way. At Teck, you’ll find purpose-driven work, a culture of respect and inclusion, and the opportunity to grow your career while helping build a better world. Apply with us Take the next step in your career by applying for the Data Scientist III role. We review applications on a rolling basis and encourage you to apply, even if your background doesn’t match every requirement. We value diversity and are committed to an inclusive, barrier-free hiring process. Reasonable accommodations are available upon request. Requisition ID: 54038 | Job Category: Technology | Employment Type: Regular Full Time | Location: Vancouver | Workplace Type: - Hybrid

Ce que vous ferez

Design, develop, and deploy machine learning and Generative AI solutions within production environments. Collaborate with cross-functional teams to translate business challenges into scalable, data-driven solutions and maintain robust MLOps workflows.

Exigences

Requires a Master's or PhD in a quantitative field and over 5 years of experience in data science and statistical modeling. Proficiency in Python, ML frameworks, cloud platforms like Azure, and experience productionizing ML solutions is essential.

Compétences indiquées

• Microsoft Azure · Souhaitée
• Docker · Souhaitée
• Apprentissage automatique · Souhaitée
• Communication · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Statistical Modeling
• Machine Learning
• Generative AI
• MLOps
• Python
• Scikit-learn
• Microsoft Azure
• Databricks
• Docker
• Causal Inference
• Data Engineering
• CI/CD for ML
• Model Monitoring
• Distributed Systems
• Industrial Analytics
• Communication

Domaines d’emploi

• Data & Analytics
• Technology
• Science & Research
• Engineering