Director, AI & Data Science (Marketing Measurement & Effectiveness)

Welcome to the Jungle•Montreal, QC

6d•$200,000•Hybrid

About The Position

Artefact is an applied AI company that builds production-ready systems for clients. With a global presence across 27 countries and a client base of over 1,000, including major consumer brands, Artefact focuses on delivering AI solutions that are integrated into clients' own cloud environments and maintained post-delivery. The company differentiates itself by possessing the data at enterprise scale, an applied AI team capable of deploying models into governed production environments, and the transformation expertise to ensure client adoption. The role specifically addresses the growing need in marketing and commerce for solutions that can determine visibility and prove effectiveness in an evolving digital landscape where traditional metrics are becoming less meaningful.

Requirements

Approximately 10+ years of experience building Marketing Mix Modeling, incrementality testing, attribution, applied statistics, causal inference, experimentation, and marketing optimization.
Proven track record of shipping models that influenced real budget allocation, with the ability to discuss both successful and failed projects.
Genuine marketing fluency, understanding differences between media channels, the impact of brand building, and the practical application of measurement outputs for media planners.
Strong data science skills, including practical experience with causal inference, Bayesian methods, forecasting, optimization, experimentation platforms, and applied GenAI.
Experience shipping generative AI or agentic AI applications into production for marketing, analytics, and decision-making.
Proficiency in coding, with a preference for debugging code directly.
Executive-grade communication skills, capable of making rigorous methodology understandable to executives and business stakeholders.
Ability to defend analytical approaches with skeptical senior stakeholders.
Hands-on program leadership experience, managing complex and ambiguous measurement programs.
Ability to challenge methodologies, review models, and solve technical problems directly.
Experience leading and developing data science teams across multiple workstreams.
Consulting and commercial mindset, including shaping solutions, supporting proposals, and expanding client relationships.
Experience working in client environments from day zero and staying post-launch.
Production instincts, with an understanding of MLOps and cloud industrialization.
AI-native ways of working, using AI daily in one's own work.
Master's degree (or higher) in computer science, engineering, statistics/mathematics, or a related field, or equivalent research/industry experience.

Nice To Haves

Financial-services experience, particularly in banking, wealth management, asset management, credit cards, or insurance.
Consulting, agency, measurement-vendor, or platform background in data-intensive industries (retail, CPG, healthcare, financial services).
Experience with brand and long-term marketing measurement (brand tracking, brand equity, long-term effects).
Experience with major media platforms and ecosystems (Google, Meta, retail media, CTV) and their measurement products.
Evidence of external thought leadership (white papers, published methodologies, conference participation, development of reusable measurement offerings).
Experience with visualization and delivery tooling (Looker, Tableau, Power BI or equivalent).
Experience with cloud data platforms (BigQuery, Snowflake, Databricks).

Responsibilities

Lead marketing measurement programs, including the design, execution, and interpretation of Marketing Mix Modeling (MMM), geo-lift testing, incrementality testing, attribution, experimentation, and marketing optimization.
Own the statistical modeling architecture and scientific rigor, including model specification, validation, calibration against live experimental results, handling uncertainty, and assumption identification.
Adapt measurement frameworks to complex commercial realities such as long consideration cycles, CRM-driven demand, short campaign flights, campaign overlap, brand and long-term effects, channel and regional constraints, and privacy-constrained measurement.
Translate model outputs into actionable recommendations for media investment, budget allocation, and scenario planning.
Work in the client's environment from day one, staying post-launch to address production issues and ensure models are functioning correctly.
Build and deploy Generative AI (GenAI) and agentic AI applications into production to transform measurement processes, including automated model diagnostics, insight generation, analyst copilots, and conversational access to measurement results.
Contribute to Artefact's reusable measurement offerings, accelerators, and intellectual property.
Collaborate with frontier labs (Anthropic, Google, OpenAI, Mistral) on early-stage AI development and implementation.
Lead and develop data scientists and analysts across multiple workstreams, focusing on growing senior talent.
Set delivery standards for reproducibility, documentation, QA, and validation of analytical deliverables.
Collaborate with scientists, engineers, creatives, and strategists to refine and implement models.
Shape solutions, support proposals, and scope new work to expand client relationships beyond the initial mandate.
Represent Artefact externally through white papers, conference talks, and published methodologies.
Contribute to productization decisions for measurement offerings, including go-to-market strategies.
Engage directly with senior client stakeholders, presenting, defending methodologies, owning recommendations, and participating in qualification and solution design.