Who We Are

Olympic Industries ULC is a leading international forest products trading company with our annual revenue exceeding $500 million. Our expertise includes the trading, importing/exporting, and manufacturing of forest products from the comfort of our office located in the heart of the vibrant and breathtaking Lonsdale Quay in North Vancouver, BC.

Established in 1972, we have a strong record of success and a clear vision for our industry's sustainable future. With a team of over 65 individuals, we are proud to have a corporate culture that rewards hard work, entrepreneurship, and team collaboration.

What We Offer

• Salary Range $70,000 to $80,000 pending relevant experience.
• Hybrid work environment. 
• Work hard, play hard company culture.
• Extended health benefits.
• Employee Wellness Spending Account.
• Life insurance and Accidental Death & Dismemberment Insurance.
• Long-term disability insurance.
• Employee assistance program.
• Educational assistance and scholarship programs.
• Employee stock ownership plan.
• RRSP Contribution Plan.
• On-site gym and showers.
• On-site kitchen with a Nespresso coffee bar.
• Easy access to the mountains and oceans.

The Opportunity

Olympic Industries ULC is a leading forest products trading firm that leverages data-driven insights to make predictions and mitigate risk in our business. As part of our growth strategy, we are seeking a highly skilled and motivated Data Scientist to join our dynamic Data Team! The Data Scientist will collaborate closely with cross-functional teams to translate business challenges into data-driven solutions.

Specific Responsibilities

The Data Scientist will be responsible for the below, as well as other related duties as assigned to support the business objectives and purpose of the company:

• Develop, construct, test, and maintain optimal data pipeline architecture.
• Identify, design, and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes.
• Develop and manage well-functioning databases and applications.
• Assist in code optimization in data science and trading projects.
• Troubleshoot and debug automation and scraping program code.
• Develop, test, and implement machine learning models using Python and other relevant tools and technologies.
• Work closely with our data engineering team to ensure that our data pipelines are optimized for machine learning applications.
• Stay up-to-date with the latest advancements in machine learning and related fields, and identify opportunities for applying these advancements to our business.

Who We’re Looking For

• An academic background in Computer Science, Software/Computer Engineering, or a related technical field.
• 2+ years of experience in writing complex SQL queries and working with databases, such as MSSQL, MySQL, PostgreSQL, and MongoDB.
• 2+ years of experience in machine learning and data mining including libraries such as TensorFlow, Scikit-learn, and XGBoost.
• Extremely strong programming skills in Python and data science libraries such as Pandas, NumPy, Seaborn, and Matplotlib.
• Working knowledge of data structures and algorithm designs.
• Working knowledge of machine learning models and deep learning algorithms.
• Familiarity with pulling data from API’s and ETL processing.
• Knowledge or experience in working with REST API and Web Socket to extract, manipulate, and automate data.
• Experience in back-end web frameworks such as Node, Django, and/or Flask considered an asset.

Apply Now!

For more information on Olympic Industries, please visit our website at www.olympicind.com.

We thank all applicants for their interest! However, only those selected for an interview will be contacted. At Olympic Industries, we embrace diversity and are committed to building a team that represents a variety of backgrounds, cultures, perspectives, skills, and experiences. As an equal opportunity employer, we encourage applications from all qualified individuals.

Please visit our careers page to see more job opportunities.