Sglottery
Senior Data Scientist
Montreal, Canada · Senior
Sponsorship not specifiedDetected 7 days ago
PythonSQLDatabricksMachine LearningTensorFlowPyTorchscikit-learnPandasData AnalysisData ScienceStatisticsA/B TestingForecastingResearchLeadershipCommunicationDemand Planning
About the role
- This is a hands-on builder role for candidates who thrive in ambiguity, move quickly from idea to production, and are energized by turning complex business problems into scalable data products.
- The role requires strong end-to-end ownership from problem framing and modeling through
- production deployment using self-service ML platform tooling.
Responsibilities
- You will work closely with Staff and Principal Data Scientists to deliver production-grade systems across forecasting, experimentation, constrained optimization, pricing, and batch and real-time recommendation systems.
Requirements
- Master's degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Operations Research, Economics, or another related STEM field
- About the Role
- We are looking for a founding Senior Data Scientist to help build high-impact decision systems in a fast- paced, startup-style environment within a large organization. This is a hands-on builder role for candidates who thrive in ambiguity, move quickly from idea to production, and are energized by turning complex business problems into scalable data products.
- You will work closely with Staff and Principal Data Scientists to deliver production-grade systems across forecasting, experimentation, constrained optimization, pricing, and batch and real-time recommendation systems. The role requires strong end-to-end ownership from problem framing and modeling through production deployment using self-service ML platform tooling.
- This role is based out of Toronto
- Design, build, and deploy end-to-end decision science systems spanning demand forecasting, experimentation, portfolio optimization, pricing, and recommendation systems
- Build batch and real-time recommendation pipelines using multi-stage cascading ranking architecture, including candidate generation, pre-ranking, ranking, and re-ranking
- Translate ambiguous business problems into structured hypotheses, measurable KPIs, experimentation plans, and production solutions
- Partner closely with MLEs to leverage self-service deployment tooling, observability, shadow deployment, canary rollout, and KPI monitoring workflows
- Own one or more domain problem areas end-to-end, driving measurable business impact through fast iteration cycles
- Contribute to modeling standards, code quality, validation rigor, and experimentation best practices established by Staff and Principal DS leadership
Nice to have
- Experience as an early or founding Data Scientist in a new team or product area
- Hands-on portfolio optimization, assortment optimization, payout optimization, or mathematical programming
- Experience with personalization, gaming, retail, marketplace, or digital consumer decision systems
- Familiarity with Databricks, PySpark, MLflow, experimentation tooling, and cloud-native deployment workflows
- Strong product intuition for balancing revenue, engagement, margin, and responsible use constraints
- If you'd like more information about your equal employment opportunity rights as an applicant under the law, please click here for EEOC Poster.
Skills
- Strong Python proficiency across pandas, scikit-learn, PyTorch, and TensorFlow
- Strong SQL and large-scale data manipulation experience
- Solid grounding in statistical modeling, machine learning, experimentation, and optimization
- Familiarity with multi-stage ranking systems, ANN retrieval, embeddings, and vector search is strongly preferred
- Strong communication skills with ability to present complex findings to business and technical stakeholders
- Collaborative mindset with ability to work cross-functionally with DS, MLE, and product teams
- Strong execution bias and comfort with rapid iteration under ambiguity
Company info
- We are looking for a founding Senior Data Scientist to help build high-impact decision systems in a fast- paced, startup-style environment within a large organization.
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