Senior Manager, GTM Data Science (AI)

Location: Toronto, Ontario, Canada

Salary: CAD 158,000–231,000 per year base salary

Company

hirify.global develops software that helps innovators design and create buildings, products, factories, and media.

What you will do

• Lead the data science team and shape the multi-quarter roadmap for customer engagement and decision intelligence initiatives.
• Partner with Sales, Marketing, and Customer Success leaders to identify high-value decisions and translate them into analytical problem statements, intervention strategies, metrics, and business cases.
• Own the lifecycle of machine learning and analytical products, from data readiness and modeling through deployment, workflow integration, experimentation, monitoring, and impact measurement.
• Manage a portfolio covering retention and churn, growth potential, upsell and cross-sell, segmentation, lead prioritization, attribution, benchmarking, simulations, and next-best action.
• Set technical and operating standards for model quality, evaluation, calibration, explainability, fairness, reproducibility, and drift monitoring.
• Recruit, coach, retain, and develop data scientists while building organizational capabilities, operating practices, and cross-functional partnerships.

Requirements

• 8+ years of experience in data science, machine learning, advanced analytics, or a related quantitative field.
• 3+ years of experience managing data science, machine learning, or advanced analytics teams.
• Advanced degree in statistics, mathematics, economics, computer science, engineering, or a related discipline, or equivalent practical experience.
• Strong technical fluency in Python or R and SQL, with expertise in statistical modeling, machine learning, experimentation, causal inference, and model evaluation.
• Experience taking analytical or machine learning products from ambiguous business problems through development, deployment, adoption, and measurable impact.
• Strong communication, stakeholder influence, judgment, ownership, and cross-functional execution skills.

Nice to have

• Experience with B2B SaaS, subscriptions, customer lifecycle analytics, or commercial analytics.
• Experience with decision intelligence, next-best action, propensity modeling, prioritization, or analytical products embedded in operational workflows.
• Experience with production machine learning, model monitoring, retraining, and collaboration with engineering or MLOps teams.
• Experience managing analytical product portfolios and developing senior technical talent.

Culture & Benefits

• Inclusive environment focused on belonging, curiosity, continuous learning, rigorous technical discussion, and collaboration.
• Compensation may include annual bonuses, stock grants, and comprehensive benefits.
• In-person onboarding and/or identity verification may be required.