Canada Channel Sales Data Scientist – Apple – Toronto, ON

Apple’s Channel Sales team in Canada is looking for a Data Scientist with serious analytics-engineering depth to join their Toronto office. This isn’t a passive reporting role — it’s a hands-on builder position at the intersection of data engineering, statistical modelling, and real-world business impact, working alongside Sales, Finance, and Worldwide counterparts to shape how Apple understands and acts on channel data across Canada.

Day-to-day, you’ll be architecting multi-stage data pipelines, owning the semantic layer and metric contracts, and deploying causal-inference and statistical methods that help answer the hard questions — pricing elasticity, demand-signal decomposition, partner planning — all while serving as the regional lead on Apple’s global AI and data roadmap.

About the Role: Canada Channel Sales Data Scientist

At the core of this position is the responsibility to build and maintain single-source-of-truth data layers that Sales, Finance, and channel teams actually trust. You’ll design and deploy executive-ready dashboards, curated metrics, and self-service BI tools, while standardising key definitions like sell-through and contribution margin across the organisation. Your pipelines will power forecasting, pricing decisions, and channel performance tracking at scale.

Beyond the technical build, you’ll be expected to collaborate with distributed engineering teams, mentor peers through code reviews, maintain architecture decision records and runbooks, and work with Worldwide teams to localise global AI initiatives for the Canadian market. Keeping pace with emerging technologies — including LLMs and agentic tooling — is a core part of staying effective in this role.

Benefits and Salary

Apple offers a base pay range of $106,100 to $159,200 CAD for this role, with your actual pay depending on your skills, qualifications, experience, and location. Qualified candidates can expect a hiring rate up to the midpoint of the range, with the possibility of higher compensation for exceptional experience. On top of base pay, employees may be eligible for discretionary bonuses or commission payments, as well as relocation support. Apple’s broader compensation package includes participation in the Employee Stock Purchase Plan and eligibility for restricted stock unit award recommendations. Additional benefits include comprehensive medical and dental coverage, retirement benefits, discounts on Apple products and services, and tuition reimbursement for formal education related to career growth at Apple.

Responsibilities

This role requires you to work across the full data lifecycle — from raw pipeline architecture through to business-ready insights. You’ll be equally comfortable writing production-grade code and presenting findings to senior business leaders, with the goal of turning complex channel data into decisions Apple Canada can act on.

• Architect and own multi-stage data pipelines on modern cloud warehouses using advanced SQL
• Build and maintain a semantic layer with metric and grain contracts for forecasting, pricing, and channel performance — standardising definitions trusted across Sales, Finance, and channel teams
• Design and deploy statistical and causal-inference methods (price elasticity, demand-signal decomposition, affordability modelling) to surface actionable recommendations
• Develop executive-ready dashboards and self-service BI tools, supported by curated data sources and data dictionaries
• Leverage LLMs and agentic tools (e.g., text-to-SQL, retrieval-augmented querying) as a productivity layer, with rigorous evals to verify correctness
• Collaborate with engineering teams to productionalize models and maintain robust data pipelines
• Act as regional subject matter expert for global AI initiatives, localising tools and solutions for the Canadian business
• Maintain documentation including architecture decision records, design docs, and runbooks; mentor peers through code reviews and modelling standards
• Translate undefined business questions into well-defined technical and analytical requirements in collaboration with Sales, Finance, and WW stakeholders

Requirements / Skills

Apple is looking for a candidate who brings both engineering rigour and business-facing communication skills to the table. The ideal person has a track record of delivering measurable impact in industry settings — not just research — and can operate confidently across technical and non-technical audiences.

• 3+ years of experience in Data Science, Analytics Engineering, ML, or Data Translation roles with demonstrated industry impact
• Degree in a quantitative field (Computer Science, Data Science, Statistics, Mathematics, or related) or equivalent professional experience
• Strong Python skills for analysis and production-grade code, including pandas, scikit-learn, REST API integration, and connector libraries
• Expert SQL on modern cloud warehouses (Snowflake, Databricks SQL, etc.) including advanced WINDOW functions, point-in-time joins, and defensive NULL handling
• Semantic layer and metric contract expertise — curated views, reusable KPIs, data contracts, and headless-BI / metrics-layer patterns
• Statistical and causal-inference fluency — experimental design, instrumental variables, A/B and natural experiments, fiscal-calendar alignment, YoY architectures
• Modern engineering practices — Git version control, docs-as-code discipline, LLM-assisted tooling with prompt engineering and hallucination mitigation

How to Apply

To apply, visit the official Apple job posting using the link below. Make sure your resume is up to date and reflects your experience with data pipelines, analytics engineering, and statistical modelling before submitting.

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