About the role

  • Senior Data Scientist at Plusgrade leveraging machine learning for dynamic pricing and offer allocation. Collaborating with cross-functional teams to enhance data-driven decision-making across diverse environments.

Responsibilities

  • Drive significant incremental business value by leveraging advanced machine learning to design, test, and implement advanced data science approaches for dynamic pricing, real-time offer allocation, and personalization, improving targeting and offer assignment within our marketing engine.
  • Develop and optimize algorithms that balance business constraints, customer behavior, and engagement objectives to deliver optimal, data-driven decisions across offers and pricing.
  • Design, enhance, and generalize models into scalable solutions that can be applied across products, partners, and diverse data environments.
  • Leverage a wide range of data sources (e.g., partner, product, and third-party data) to enrich algorithms and clearly demonstrate measurable business impact.
  • Lead and collaborate with cross-functional teams (Product, Engineering, Analytics) to establish best practices for developing, automating, and standardizing advanced data science solutions, with an emphasis on real-time applications.
  • Champion scalable, automated production deployments by integrating algorithms into live systems through rapid iteration and experimentation, leveraging AWS infrastructure (particularly SageMaker) to deploy, monitor, and scale models in production.

Requirements

  • 4+ years of experience researching, designing, and developing machine learning algorithms, with a strong focus on solving real-world business problems.
  • Expertise in developing algorithms for real-time decision-making or dynamic optimization problems, such as offer allocation, continuous pricing, or recommender systems.
  • Proficiency in machine learning, large-scale data processing, predictive analytics, and optimization techniques.
  • Strong programming skills in Python, with hands-on experience using machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Advanced SQL skills and familiarity with relational databases, enabling efficient manipulation of large and complex datasets.
  • Hands-on experience working in AWS environments, particularly with SageMaker for building, training, deploying, and monitoring machine learning models at scale.
  • The ability to conceptualize, design, and communicate complex algorithms to technical and non-technical stakeholders clearly and concisely.
  • Innate curiosity to solve complex problems, derive actionable insights and iterate on innovative solutions.
  • Strong business acumen and an ability to align data science initiatives with commercial goals, ensuring measurable business impact.
  • A quantitative Master's or Ph.D. is required, or equivalent experience. Relevant fields include, but are not limited to, Computer Science, Engineering, Mathematics, Statistics, and Operations Research.

Benefits

  • RRSP/401(k) Matching
  • Comprehensive Health Plans
  • Flexible Paid Time Off
  • Travel Experience Credit
  • Annual Wellness Credit
  • Team Events
  • Commuter Credit
  • Work From Anywhere Program
  • Parental Leave Top Up
  • Adventure Pass

Job type

Full Time

Experience level

Senior

Salary

Not specified

Degree requirement

Postgraduate Degree

Tech skills

AWSPythonPyTorchScikit-LearnSQLTensorflow

Location requirements

HybridMontrealCanada

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