Data Scientist

BC Ferries•Delta, BC

5d•CA$83,500 - CA$104,300•Hybrid

About The Position

At BC Ferries, data is helping shape the future of one of British Columbia's most essential transportation networks. Every day, millions of data points are generated across our vessels, terminals, customers, and operations. We're looking for a curious, innovative Data Scientist who is excited to turn that data into meaningful insights, predictive models, AI-powered solutions, and digital products that improve how we serve coastal communities. As part of our Enterprise Optimization, Data & Insights team, you'll work on high-impact initiatives that span forecasting, machine learning, artificial intelligence, digital twins, operational optimization, customer experience, and enterprise analytics. This is an opportunity to apply advanced data science in an environment where your work will influence strategic decisions, improve operational performance, and help shape the future of BC Ferries. If you're passionate about solving complex business problems, building production-ready machine learning solutions, and collaborating with talented business and technology professionals, we'd love to hear from you.

Requirements

Master’s Degree in Computer Science, Data Science, Statistics, Machine Learning, Artificial Intelligence, Engineering, Economics or other related discipline
Certifications such as Microsoft Certified Azure Data Scientist Associate, IBM Data Science Professional Certificate etc.
Minimum 4+ years of recent and related experience in developing advanced analytics and machine learning solutions using Python, SQL, and modern data science tools
Experience building predictive models using techniques such as regression, decision trees, random forests, gradient boosting, support vector machines, principal component analysis, deep learning, and time series forecasting
Experience working with structured and unstructured data, statistical modelling, natural language processing, and advanced AI and machine learning techniques
Familiarity with cloud platforms, big data technologies, Git-based version control, and production-ready analytics environments
Strong communication and stakeholder engagement skills, with the ability to present complex analytical findings in a clear and compelling way.
Strong knowledge with relational databases & structured query language (SQL)
Experience with cutting-edge machine learning and deep learning models, techniques and tools
Understanding of natural language processing (NLP), time series analysis or reinforcement learning
Experience in algorithms like logistic regression, gradient boosted machines, decision trees, random forests, support vector machines (SVM), principal component analysis (PCA), deep neural networks
Ability to process and analyze structured and unstructured data
Experience with one of the major cloud computing platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS) and Microsoft Azure
Experience launching, planning and executing data science projects
Proven experience and solid understanding of mathematical and statistical modelling; inference, Bayesian methods, likelihood estimation, sampling theory and hypothesis testing
Working experience with distributed version control systems such as Git and GitHub
Familiarity with big data tools (Spark, Hadoop)

Responsibilities

Assisting in collecting, processing, and analyzing large datasets to uncover insights
Supporting the development and implementation of machine learning models and algorithms
Collaborating with other data expertise and cross-functional teams to understand business needs and contribute to data-driven solutions
Creating data visualizations and reports to communicate findings to stakeholders
Conducting exploratory data analysis to identify trends and patterns
Maintaining data quality and integrity throughout the data lifecycle
Supporting the establishment and maintenance of data governance practice, ensuring compliance with data policies and standards
Staying updated with the latest trends and advancements in data science and machine learning
Investigating approved data use cases and lead the design, research, development and delivery of data products, models and deliverables by collaborating directly with teams/individuals across the company
Productionizing predictive and descriptive machine learning models in the field of time series analysis and forecasting for demand forecasts
Exploring, designing, and building AI prototypes to significantly improve customer experience
Using advanced statistics to develop, build and maintain data models to explain subtle trends in business performance
Working collaboratively in a multi-disciplinary team environment establishes and maintaining professional networks with subject matter experts
Presenting results to senior leadership in a compelling and clear manner to drive business decision-making