Sglottery
Staff Data Scientist
Montreal, Canada · Staff+
Sponsorship not specifiedDetected 5 days ago
PythonSQLDatabricksMachine LearningTensorFlowPyTorchscikit-learnPandasData AnalysisData ScienceStatisticsA/B TestingProduct StrategyForecastingResearchLeadershipMentoring
About the role
- As an early senior technical leader, you will work closely with the Principal
- This role sits at the intersection of technical depth, platform leverage, and strategic execution.
Responsibilities
- Lead the design and delivery of high-impact decision science systems across forecasting, constrained optimization, experimentation, and batch and real-time recommendation systems
- Partner with the Principal Data Scientist to establish modeling standards, experimentation guardrails, validation frameworks, and deployment playbooks for the founding DS organization
- Build production-grade decision engines spanning player personalization, next-best-action systems, pricing, portfolio optimization, and retail recommendation use cases
- Drive the design of multi-stage recommendation and ranking architectures, including retrieval, pre-ranking, ranking, and re-ranking
Requirements
- Master's degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Operations Research, Economics, or another related STEM field
- Proven experience leading ambiguous, high-impact data science initiatives from framing through production business impact
- About the Role
- We are looking for a founding Staff Data Scientist to help build the decision science function from the ground up and translate our long-term product and decisioning vision into scalable production systems. This is not a maintenance role. As an early senior technical leader, you will work closely with the Principal
- Data Scientist, Staff peers, and Senior Data Scientists to define the modeling standards, decision science patterns, and execution playbooks that will become the backbone of the organization.
- This role sits at the intersection of technical depth, platform leverage, and strategic execution. Despite being part of a large organization, the team operates with a startup mindset: fast-paced, highly iterative, and biased toward rapid execution, learning, and measurable business impact. You will own some of the organization's highest-value problems across forecasting, experimentation, personalization, recommendation systems, portfolio optimization, pricing, and player decision systems.
- This role is based out of Toronto.
Nice to have
- Experience as a founding or early senior hire in a new DS organization
- Hands-on portfolio optimization, payout optimization, assortment optimization, or mathematical programming
- Experience with personalization, gaming, retail, marketplace, or digital consumer decision systems
- Experience working with self-service experimentation and ML platforms
- Familiarity with Databricks, PySpark, MLflow, and cloud-native deployment workflows
- Strong product intuition for balancing revenue, margin, player engagement, and responsible gaming 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
- Deep expertise in statistical modeling, experimentation, causal inference, and optimization
- Strong SQL and large-scale data experience
- Familiarity with multi-stage cascading ranking architectures and decision APIs
- Ability to translate long-term product vision into executable decision science roadmaps
- Strong technical mentorship and review discipline
- Ability to influence DS standards, experimentation culture, and KPI rigor across the founding team
- Translate ambiguous business opportunities into structured modeling roadmaps, milestones, and measurable KPI frameworks
Benefits
- We are looking for a founding Staff Data Scientist to help build the decision science function from the ground up and translate our long-term product and decisioning vision into scalable production systems.
- 6+ years post-Master's experience or 4+ years post-PhD experience in data science, decision science, econometrics, or applied machine learning
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This listing is sourced directly from Sglottery's careers page and normalized into a canonical job model.