Job Description

Locations

• Canada, ON, Toronto, Toronto, ON, Canada

Salary

Skills Required

• - 3+ years of building machine learning models for business application experienceintermediate
• - PhD, or Master's degree and 6+ years of applied research experienceintermediate
• - Experience programming in Java, C++, Python or related languageintermediate
• - Experience with neural deep learning methods and machine learningintermediate

Required Qualifications

• - 3+ years of building machine learning models for business application experience (experience, 3 years)
• - PhD, or Master's degree and 6+ years of applied research experience (experience, 6 years)
• - Experience programming in Java, C++, Python or related language (experience)
• - Experience with neural deep learning methods and machine learning (experience)

Preferred Qualifications

• - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. (experience)
• - Experience with large scale distributed systems such as Hadoop, Spark etc. (experience)
• - Experience in working with Agentic AI and Gen AI applications (experience)

Responsibilities

• As An Applied Scientist On This Team, You Will
• 1. Serve as the technical leader in Machine Learning, guiding efforts within the team and collaborating with other teams.
• 2. Conduct hands-on analysis and modeling of large-scale data to generate insights that boost traffic monetization and merchandise sales while maintaining a positive shopper experience.
• 3. Lead end-to-end Machine Learning projects that involve high levels of ambiguity, scale, and complexity.
• 4. Build, experiment, optimize, and deploy machine learning models, collaborating with software engineers to bring your models into production.
• 5. Run A/B experiments, gather data, and perform statistical analysis to validate your models.
• 6. Develop scalable and automated processes for large-scale data analysis, model development, validation, and serving.
• 7. Explore and research innovative machine learning approaches to push the boundaries of what’s possible.
• About the team
• The Media Planning Science team builds and deploys models that provide insights and recommendations for media planning. Our mission is to assist advertisers in activating plans that align with their goals. Our insights and recommendations leverage heuristic and machine learning models to simplify the complex tasks of forecasting, outcome prediction, budget planning, optimized audience selection and measurements for media planners. We integrate our insights into user interfaces and programmatic integrations via APIs, ensuring reliable data, timely delivery, and optimal advertising outcomes for our advertisers.

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