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Added 35 mins ago
M
AI Opportunities | Opportunités en IA
McKesson
Montreal, QC
- Full-time
Added 1 hour ago
Senior Data Scientist
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Added 1 hour ago
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Toronto, ON · AMER - Canada - Ontario - Toronto - University Ave
- Full-time
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Added 2 hours ago
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AB · Edmonton, AB
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Data Scientist II
TD
Toronto, ON
- Full-time
Added 2 hours ago
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…systems onto modern, cloud-based platforms. They need a hands-on Data Architect to design a data architecture on Azure that's scalable, secure and well governed, and that supports…
Added 2 hours ago
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The Senior Data Architect is responsible for defining and leading the segment data architecture strategy that enables trusted, scalable, secure, and AI-ready data capabilities across the…
Added 2 hours ago
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Senior Data Scientist role within our client's Advanced Analytics team. This posting is for two headcount and both are end-to-end data science roles and are interchangeable by design.
Added 4 hours ago
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As a data scientist at Ubisoft Montréal, you will contribute to a technology produc
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Have 8–10 years of data science/analytics experience.
Added 5 hours ago
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Added 9 hours ago
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Lighthouse Lab Services is currently seeking a dedicated and detail-oriented R&D Bioanalytical Scientist / LC-MS Leader to join our client in Laval, QC. This is a full-time position.
Added 16 hours ago
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- Full-time
Role Description: Design and implement scalable, secure and efficient enterprise data architectures aligned with business requirement and also architect modern data warehouse, data lakes,…
Added 17 hours ago
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Added 18 hours ago
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Toronto, ON · Markham, ON
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HISH IT SERVICES

Data Scientist

Toronto, ON, Canada

$85 CAD / hour · Contract

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Job details

Pay: $85 CAD / hour
Job type: Contract
Apply by: Nov 5, 2026
Posting language: English
Posted: Oct 6, 2026

Original job description

Role : Data Scientist

Location: 2-day(Toronto)

Job type: Contract(6 Months) - High possibility of Extension

Pay : CAD $85 /Hour

Start date : Immediate

Role Overview

The Senior Analytics & Insights Consultant sits within Adastra's AI practice and serves as an embedded, end-to-end analytics partner to client businesses, translating deep quantitative analysis into strategy that senior stakeholders can act on. Leveraging strong applied statistics across segmentation, uplift and propensity modeling, forecasting, and profitability analytics, you will help clients mine their data, surface opportunities, and design the experiments and attribution models that prove what works. The preliminary responsibilities will be on customer and marketing analytics: shaping audience and distribution strategy and measuring tactics end-to-end while partnering with execution teams rather than owning execution yourself. You will build trusted relationships, tell a clear story with data, and work fluently across a modern analytics stack including Azure, Databricks, and Python alongside established Oracle and SAS environments.

Responsibilities

· Serve as an embedded, end-to-end analytics partner, owning strategy, analysis, and measurement while working closely with execution teams rather than executing directly.

· Build and maintain analytical models including segmentation, uplift and propensity models, forecasting, and profitability analytics to surface and prioritize opportunities.

· Define KPIs and funnel metrics, and maintain a singular, ongoing view of performance from measurement pipeline through tactical outcome.

· Partner with execution teams to jointly design experiments, then own the attribution models and monitoring that measure their results.

· Mine the client base to understand behaviors, portfolio, and market context, and advise on audience strategy and how to move clients toward specific actions.

· Present findings to executive stakeholders, telling a clear story with data and becoming a consultant the business depends on for strategic decisions.

· Operate independently across a modernizing stack (Azure, Databricks, Python, Oracle, SAS) and within client MarTech ecosystems such as Salesforce and Adobe Analytics.

Qualifications

· Undergraduate degree in statistics, economics, mathematics, or a related quantitative field; master's or equivalent applied experience preferred.

· 7+ years in applied analytics, marketing science, or a comparable quantitative consulting or strategy role, including senior stakeholder-facing work.

· Strong applied statistics expertise across segmentation, uplift and propensity modeling, forecasting, and profitability analytics.

· Hands-on experience designing experiments, building attribution models, and measuring performance end-to-end.

· Proficiency in Python for analytics with experience across cloud platforms such as Azure and Databricks; Oracle and SAS familiarity an asset.

· Ability to translate complex analysis into a clear narrative for technical and non-technical audiences.

· Self-starter able to operate independently and own engagements end-to-end within a lean, senior team.

· Experience with marketing technology such as Salesforce and Adobe Analytics is an asset.

Apply About employer

More about this job

Responsibilities

Partner with client businesses to develop analytical strategies, build models, define performance metrics, and measure outcomes through experiments and attribution. Analyze customer and marketing data, advise on audience strategy, and present actionable findings to senior stakeholders.

Requirements

Requires an undergraduate degree in a quantitative field and at least seven years of applied analytics, marketing science, or comparable consulting experience; a master's degree or equivalent applied experience is preferred. Candidates should have strong applied statistics and hands-on experience with experiments, attribution, Python, and cloud analytics platforms, along with the ability to communicate findings and work independently.

Skills

Applied Statistics
Customer Analytics
Marketing Analytics
Segmentation
Uplift Modeling
Propensity Modeling
Forecasting
Profitability Analytics
Experiment Design
Attribution Modeling
KPI Definition
Python
Azure
Databricks
Oracle
SAS

Visa sponsorship

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Keywords

Applied Statistics
Customer Analytics
Marketing Analytics
Segmentation
Uplift Modeling
Propensity Modeling
Forecasting
Profitability Analytics
Experiment Design
Attribution Modeling
KPI Definition
Funnel Metrics
Performance Measurement
Python
Azure
Databricks
Oracle
SAS
Salesforce
Adobe Analytics
Audience Strategy
Marketing Science
Analytics Consulting
Executive Stakeholder Communication

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