Intern, Low Carbon Strategy – January 2027 (8 or 12-Month Term)

Sunoco LP; Calgary; Sur place; CAD 25 000 - 36 000; Plein temps

Résumé du poste

Sunoco LP is seeking a Low Carbon Strategy Analyst to support its Low Carbon Strategy team within the Supply & Trading division. This role will work towards automating low carbon market models and forecasting processes, improving existing models and increasing automation.

The successful candidate will gain exposure to major negotiation, optimization and investment decisions in the low carbon fuels and credits space.

Qualifications

• Must be enrolled in a Canadian post-secondary program in a data-related field.
• Strong data science skills with Excel macros, R and RStudio.
• Experience with market modeling, forecasting, and automation.
• Interest in fuel industry or environmental commodities.

Responsabilités

• Automate market analytics to support decision making.
• Automate low carbon market reporting and forecasting using Excel macros, R and RStudio.
• Analyze low carbon market challenges using economic models to assess market value.
• Provide insights and data-driven recommendations to support Sunoco's Low Carbon Strategy.
• Collaborate with the team to optimize and improve market models for greater efficiency.
• Enhance and expand performance of existing models using automation platforms.

Connaissances

Data science

Forecasting

Market analysis

Automation

Formation

Data science / statistics degree

Outils

Excel macros

R

RStudio

Description du poste

Description

Position at Parkland Corporation

As of November 1, 2025, Sunoco LP has successfully completed its acquisition of Parkland Corporation. For more information, please visit www.sunocolp.com.

Sunoco LP is a leading energy infrastructure and fuel distribution master limited partnership operating across 32 countries and territories in North America, the Greater Caribbean, and Europe. The Partnership’s midstream operations include an extensive network of approximately 14,000 miles of pipeline and over 160 terminals. This critical infrastructure complements the Partnership’s fuel distribution operations, which distribute over 15 billion gallons annually to approximately 11,000 Sunoco and partner-branded retail locations, as well as independent dealers and commercial customers.

At Sunoco, we take great pride in what we do and wholeheartedly believe our employees drive success for our company and our customers. We are always looking for the best and brightest talent and are committed to making your job a challenging and rewarding experience.

The Opportunity:

Sunoco is seeking a Low Carbon Strategy Analyst to support our Low Carbon Strategy team within the Supply & Trading division. This role will work towards optimizing and automating low carbon fuel market models and forecasting processes. The successful candidate will assist in improving existing models, developing new tools and increasing automation, streamline operations and enhance efficiency. The successful candidate will work within a small but very influential team of experienced strategists and get exposure to major negotiation, optimization and investment decisions in the Low Carbon fuels and credits space. The role provides direct exposure to commodity trading and commercial decision-making, offering insight into how market fundamentals, regulation, and strategy drive value creation across the low carbon and conventional fuels value chain.

Responsibilities:

• Automate market analytics to support decision making
• Automate low carbon market reporting and forecasting using Excel macros, R and RStudio to streamline workflows.
• Analyze low carbon market challenges using economic models to assess market value.
• Provide insights and data-driven recommendations to support Sunoco's Low Carbon Strategy.
• Collaborate with the team to optimize and improve market models for greater efficiency.
• Enhance and expand performance of existing models using automation platforms (e.g. Excel macros, R and RStudio).

Education:

• Currently enrolled in a Canadian post-secondary institution and pursuing a degree in Data Science, Statistics, Mathematics, Computer Programming, and Engineering.
• Preference will be given to students in their 3rd or 4th year of study with one academic term remaining following the completion of the work term.

Requirements:

• Available for an 8 or 12-month work term beginning in January 2027.
• Strong data science skills, including Excel macros, R, and RStudio.
• Experience with market modeling, forecasting, and process automation.
• Interest in or experience with the fuel industry or Environmental Commodities.
• Ability to work effectively both independently and within a team environment.

Humble. Hungry. Smart. Does this sound like you?

Do others describe you as being a down-to-earth achiever? Someone who thinks outside the box and always strives to do more than what is required? Someone who sees the bigger picture? You sound brilliant to work with!

We Want You To Shine:

We are committed to providing equal opportunities to all applicants. If you require accommodation due to a disability, you will have an opportunity to notify us when scheduling your interview.

Belonging Matters. Because You Do:

We are an equal opportunity employer and encourage applications from all qualified individuals. Our ability to work as one team across Canada, the United States, and the Caribbean is foundational to our success. We show up as our authentic selves each day and create space for one another’s unique contributions.

We respect the diverse cultures, traditions, and perspectives of Indigenous Peoples and seek to achieve equitable partnerships and opportunities with Indigenous communities.

The Fine Print:

Candidates must be legally eligible to work in the country in which they applied. Regrettably, we are unable to sponsor employment visas at this time.

Final candidates will be required to undergo a confidential pre-employment background check, including but not limited to educational, criminal, credit, drug and alcohol, and/or fitness for duty testing.