Data Science Engineer/Developer

ARC has had an exciting growth story driven by the contributions of our people, principled business strategy and high-performance culture. We are a Canadian energy company with a strong track record of operational and financial performance. Today, we are the largest pure-play Montney producer, and Canada’s third-largest natural gas producer and largest producer of condensate.

In alignment with our values, we are proud to produce Canadian energy safely and efficiently. Producing low-cost, reliable energy strengthens our resilience in the evolving global energy system, and enables ARC to create value for our people, shareholders, stakeholders and communities.

We have a long-term view and are committed to best-in-class performance in every aspect of our business. Following our guiding principles has shaped the company we are today and will underpin our success in the future. Through innovation, teamwork and a commitment to operational excellence, our diverse team of people drive our company’s success. From the office to the field, our team of talented professionals work hard each day to safely execute our business and create positive and lasting impacts for our stakeholders.

We are currently seeking a Data Science Engineer/Developer to join our dynamic Data Analytics team. Reporting to the Supervisor, Advanced Analytics, the successful candidate will play an integral part in contributing to the development and enhancement of machine learning models while assisting with operational tasks. This role combines hands-on coding and modeling responsibilities with support for production of ML pipelines, ensuring continuity and innovation in our machine learning environment.

The successful candidate will thrive in a collaborative, fast-paced team environment, balancing independent work with close coordination across Analytics and Engineering teams.

- Design, implement, and iterate on predictive models and algorithms to meet business objectives

- Train and validate models for accuracy, reliability, and performance

- Explore emerging techniques and prototype innovative solutions

Monitoring & Governance

- Implement systems to track model drift, usage, and performance metrics

- Enforce governance standards to maintain integrity and compliance

- Drive transparency through robust reporting, change management and documentation practices

Support MLOps Activities

- Maintain and optimize production ML pipelines for scalability

- Build and operate CI/CD pipelines to automate packaging, testing, and promotion of models and services

- Automate deployments and implement rigorous testing frameworks

- Ensure reliable, consistent delivery across products

Collaboration & Innovation

- Partner with business stakeholders and data engineering teams to align solutions with strategic goals

- Support delivery and adoption to existing and or new business workflows

- Ensure data is available for reporting and analytical purposes

What You Will Bring To Arc

Working with cutting edge infrastructure and tools including Databricks, Github Copilot, Azure IOT, and many more, you will solve challenging business problems requiring the application of advanced data science across Engineering, Drilling, Completions, Geosciences, Production, Operations Center, Marketing, and Environmental. In addition, the successful candidate will possess the following qualifications:

- A bachelor's or master's degree in computer science, data science, statistics, engineering, or a related field

- Minimum of 5 years’ experience architecting large scale enterprise data and machine learning solutions; responsibilities can be adapted for a more senior candidate

- Minimum of 3 years’ experience productionizing machine learning models and data pipelines following DevOps and MLOps best practices

- Proven track record of building and deploying machine learning models, such as regression, classification, time series, or deep learning

- Solid background and strong comprehension of data structures and algorithms with a proficiency in Python and PySpark

- Experience utilizing orchestration frameworks to deploy machine learning containers and endpoints

- Experience utilizing MLflow or other technologies for model tracking, deployments, serving, and registry

- Strong acumen to assess ROI for each system component and a tendency to simplify workflows for the sake of maintainability

- Proven work experience building and deploying machine learning engineering pipelines and real-time/batch processing frameworks leveraging Databricks; experience with other cloud technologies such as Azure, AWS and GCP would be an asset

- Experience with version control systems such as git

- Excellent communication skills, enabling you to translate technical findings into practical, actionable insights

Rewarding Opportunity

- An opportunity to be part of delivering responsible energy by developing and growing your career with us

- Working collaboratively with, and learning from some of the most talented and experienced people in our industry

- A market-competitive and pay-for-performance total compensation plan, including eligibility to participate in our bonus and long-term incentive programs

- Top-tier benefits, wellness/healthcare spending accounts and savings plans

- A culture of caring and high performance

- Focus on health and well-being

- An environment where all individuals are treated fairly and respectfully, have equal access to opportunities and resources, feel a sense of belonging, and can contribute fully to the organization’s success

- Meaningful work that makes a difference in the Canadian energy industry

We thank you for your interest in ARC, however, only those candidates selected for an interview will be contacted. Accessibility accommodation for applicants is available upon request during the talent acquisition process.