Software Engineer II, Advertiser Optimization

Accountabilities:: Develop and evaluate quantitative models and algorithms for advertising bidding, pacing, and budgeting, applying mathematical, statistical, economic, or related quantitative techniques to solve complex marketplace problems at scale. Collaborate with senior scientists, engineers, and product managers to translate marketplace questions into mathematical formulations, develop analyses and prototypes, design experiments, and interpret results using large-scale datasets. Contribute to production systems by implementing, validating, monitoring, and improving algorithms, progressively taking ownership of well-scoped projects from initial hypothesis through measurable business and technical impact. Analyze rapidly changing marketplace conditions and balance analytical rigor with execution speed, adapting to evolving priorities, new challenges, and emerging opportunities. Clearly communicate assumptions, methodologies, findings, results, and limitations to both technical and cross-functional stakeholders, helping teams make informed decisions through strong analytical reasoning. Support the continuous improvement of systems responsible for real-time bidding, pacing, budgeting, targeting, and advertiser-facing recommendations within a scaled advertising marketplace. Requirements: PhD in mathematics, statistics, economics, operations research, or a related quantitative discipline, with a strong foundation in areas such as optimization, probability, statistical modeling, econometrics, or control theory. Proficiency in Python and SQL , with the ability to translate quantitative concepts into practical analyses, algorithm implementations, experiments, and production-oriented solutions. Strong analytical and problem-solving abilities, with the capacity to work through complex quantitative questions and draw meaningful conclusions from large-scale data. Excellent written and verbal communication skills, including the ability to explain assumptions, methodologies, results, and limitations clearly to technical and cross-functional audiences. 2+ years of software engineering experience, particularly experience applying quantitative methods to production systems, is preferred. Familiarity with advertising systems, auction theory, marketplace optimization, or similar decision-making problems is an advantage. Experience working with large-scale data pipelines, real-time decision systems, or production machine learning applications is highly valued. Familiarity with machine learning techniques and experience applying machine learning methods within production environments is a plus. Benefits: Competitive Canadian Compensation: Base salary range of $145,000–$153,000 CAD , with compensation varying based on permanent work location, experience, skills, and role requirements. Equity Opportunities: Eligibility for a new-hire equity grant as well as potential annual equity refresh grants. Remote Flexibility: Remote work is supported for eligible employees located in Ontario, Alberta, British Columbia, or Nova Scotia . Flexible Work Environment: Employees can choose where they do their best work, including from home, an office, or another suitable location, while participating in regular opportunities to build community in person. Professional Growth: Work alongside experienced scientists, engineers, and product managers on complex quantitative and engineering problems with measurable impact. High-Impact Technical Work: Opportunity to contribute to large-scale advertising systems involving real-time auctions, optimization, data science, and algorithmic decision-making. Competitive Benefits: Access to a market-competitive benefits package designed for employees based on their location.