ML Engineer
Toronto, ON M1R 0E9 Canada
Job Description
Role Overview
In this role you will help drive personalized experiences for customers as a ML Generalist Pricing Recommendations
Are you passionate about harnessing the power of data to drive impactful business decisions customer is seeking a ML Generalist to play a pivotal role in shaping the future of our consumer journey through cutting edge Machine Learning ML solutions for pricing and recommendations Join us and make a tangible difference in the lives of our customers by developing innovative solutions that deliver personalized experiences and optimize value
About The Role
- Full Stack ML acumen to conceptualize design and implement state of the art ML models for dynamic pricing strategies and personalized product recommendations
- Develop implement and deploy machine learning models that leverage our unique combination of user behavior and subscription data to improve consumer value
- Engineer and maintain largescale consumer behavioural feature stores while ensuring scalability and performance
- Develop and maintain data pipelines and infrastructure to support efficient and scalable ML model development and deployment
- Collaborate with cross functional teams Marketing Product Sales to ensure your solutions align with strategic objectives and deliver real world impact
- Create algorithms for optimizing consumer journeys and increasing conversion and monetization
- Design Analyze and troubleshoot controlled experiments Causal AB tests Multivariate tests to validate your solutions and measure their effectiveness
- Agile development mindset appreciating the benefit of constant iteration and improvement
- Focus on business practicality and the 8020 rule very high bar for output quality but recognize the business benefit of having something now vs perfection sometime in the future
About You
- Master’s degree PhD in Machine Learning Statistics Data Science or related quantitative fields preferred
- 3 to 5 years of experience in one or more of the following areas machine learning including deep learning recommendation systems pattern recognition data mining or artificial intelligence
- Proficiency in using casual inference uplift modeling splines support vector machines lookalike modeling model stacking ensembles embedding based modeling etc
- Proficient in Python SQL intermediate data engineering skill set with tools libraries or frameworks such as PySpark Hadoop Hive and Big Data technologies scikitlearn pandas NumPy PyTorch etc
- Experience with various ML techniques and frameworks e.g., data discretization normalization sampling linear regression decision trees deep neural networks etc
- Experience in building industry standard recommender systems and pricing models
- Experience in MLOps ML Engineering and Solution Design
Its Great But Not Required If You Also Have
- Experience working in a consumer or B2C space for a SaaS product software provider
- Experience in developing recommendation systems and deep learning-based models
- Excel in solving ambiguous and complex problems being able to navigate through uncertain situations breaking down complex challenges into manageable components and developing innovative solutions
Skills
Machine Learning-Python
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