Junior Quantitative Analyst

Glencore; Toronto; On-site; CAD 60,000 - 75,000; Full time

Job summary

A global mining and commodities company is seeking a highly analytical Junior Quantitative Analyst for their Toronto office. The role focuses on supporting decision making across sulfuric acid operations through statistical modelling, data engineering, and market analysis. The ideal candidate is a recent graduate skilled in Python and Excel with a strong interest in quantitative analysis and automation. The position offers opportunities for career development and addresses ad-hoc data requests for business presentations.

Qualifications

• Bachelor's degree in a quantitative discipline such as Computer Science, Statistics, Engineering, Mathematics or Economics.
• Advanced proficiency in Python and Excel is required.
• Experience with data analysis, statistical modelling, or machine learning techniques.
• Ability to organize tasks and drive projects from concept to completion.

Responsibilities

• Develop and maintain quantitative models related to physical commodity trading.
• Collect, clean, and analyze large datasets to identify trends.
• Implement statistical and machine learning techniques to support strategies.
• Build and maintain automation and lightweight software solutions.
• Document methodologies, assumptions, workflows, and code.

Skills

Advanced proficiency in Python

Advanced proficiency in Excel

Data analysis

Statistical modelling

Machine learning techniques

Analytical reasoning

Problem-solving

Effective communication

Organizational skills

Critical thinking

Education

Bachelor's degree in a quantitative discipline

Tools

SQL

APIs

Job description

We are seeking a highly analytical and self-driven Junior Quantitative Analyst to support commercial decision making across our North American sulfuric acid operations. This position is an ideal fit for a recent graduate with commendable quantitative and programming abilities who is keen to understand the business, build analytical tools, and pursue career development.

This role combines statistical modelling, simulation, data engineering, and market analysis to enhance data-driven decision making across trading, supply chain, and strategic planning activities. The ideal candidate will continue key analytical and modelling work while identifying new areas of improvement and approaches to support commercial operations. In addition, the role includes developing simple automation solutions to improve daily workflows and responding to ad-hoc data requests to support presentations and other business needs.

You will lead key analytical projects, working largely with minimal supervision with guidance and direction, and will report directly to the commercial trading team.

You will be expected to:

• Develop and maintain quantitative models related to physical commodity trading, including shipments, inventory levels, freight calculations, pricing trends, and other operational scenarios
• Collect, clean, and analyze large datasets to identify trends, patterns, and signals
• Implement statistical and machine learning techniques with appropriate guidance to support trading, pricing, or other commercial strategies
• Build and maintain automation tools and lightweight software solutions to streamline recurring workflows and improve data accuracy
• Complete ad-hoc data and analysis requests to support presentations, strategy discussions, and commercial decision making
• Collaborate with commercial and logistics teams to translate analytical outputs into practical recommendations
• Document methodologies, assumptions, workflows, and code to ensure clarity and continuity
• Continuously improve model accuracy, automation reliability, and analytics workflows
• Support the commercial team by developing pricing benchmarks, tracking industry trends, and preparing presentation materials
• Assist in organizing and validating commercial data including shipment records, logistics costs, and sales prices

Do you have what it takes?

• Bachelor's degree in a quantitative discipline (Computer Science, Statistics, Engineering, Mathematics, Economics, or related field)
• Advanced proficiency in Python and Excel
• Experience with data analysis, statistical modelling, or machine learning techniques
• Ability to organize tasks and drive projects from concept to completion with commercial support
• Proficient in analytical reasoning, effective data management, and problem-solving, with significant attention to detail
• Effective communication skills and ability to work collaboratively across team
• Familiarity with commodity markets is an advantage
• Knowledge of time-series analysis, Bayesian methods, and Stochastic modelling
• Exposure to quantitative research projects
• Experience with lightweight software or tool development (e.g., automated scripts, dashboards, reporting tools)
• Familiarity with SQL, APIs, or data warehouse tools
• Independent and critical thinker with the ability to question existing practices constructively.
• Highly organized and efficient, with strong work management habits.
• Motivated, curious, and committed to continuously learn and develop.
• Skilled at working on their own and understanding when it is appropriate to consult others.
• Versatile and skilled, able to handle both in-depth analytical work and practical automation alongside fast‑turnaround data tasks.

Language

Advanced proficiency in English (verbal and written).

Location

Corporate office in Toronto.

Only candidates with full working rights in Canada will be considered.

Glencore encourages diversity and provides an inclusive workplace. We provide and can arrange necessary support for applicants who may need assistance. ( [e-mail] )