Senior Manager, GTM Data Science

This is a fully remote position, open to applicants in Canada, +1 more country.

📋 Description

• Develop the multi-quarter Data Science roadmap focusing on customer engagement applications.

• Collaborate with senior leaders in Sales, Marketing, and Customer Success to prioritize key decisions that add value.

• Transform strategic inquiries into decision frameworks, analytical problem statements, intervention strategies, success metrics, and business cases.

• Provide guidance to executives and cross-functional leaders, challenge assumptions, offer recommendations, and communicate trade-offs.

• Define success metrics and ensure their adoption leading to realized business outcomes.

• Oversee a portfolio of Decision Intelligence initiatives related to retention, churn, growth, upsell, cross-sell, segmentation, propensity, lead prioritization, compliance, attribution, benchmarking, simulations, and next-best action.

• Drive initiatives from problem identification and data readiness to modeling, validation, deployment, workflow integration, experimentation, impact measurement, and monitoring.

• Collaborate with program management, analytics engineering, data engineering, product managers, and federated analytics teams.

• Establish operating rhythms and quality standards, including roadmap reviews, technical assessments, launch readiness, outcome evaluations, and risk management.

• Provide technical leadership in prediction, experimentation, causal inference, optimization, ranking, simulation, and associated methods.

• Supervise statistical modeling, machine learning, experimentation, causal methods, propensity and uplift modeling, scoring, and prioritization.

• Maintain standards for data quality, leakage prevention, model evaluation, calibration, reproducibility, explainability, fairness, drift monitoring, and performance assessment.

• Ensure that machine learning products correlate insights with actions and measurable incremental impacts.

• Keep abreast of advancements in machine learning, AI, experimentation, causal inference, and decision intelligence.

• Lead, recruit, retain, and develop a high-caliber data science team.

• Mentor senior individual contributors and upcoming leaders.

• Conduct performance and talent evaluations, provide constructive feedback, identify development opportunities, and formulate succession and hiring strategies.

• Foster an inclusive team culture emphasizing technical rigor, learning, collaboration, and accountability.

• Create reusable methods, decision frameworks, operating practices, and partnerships throughout the EDA organization.

⛳️ Requirements

• 8+ years of experience in data science, machine learning, advanced analytics, or a related quantitative field, with substantial hands-on applied experience.

• 3+ years of experience leading data science, machine learning, or advanced analytics teams.

• Advanced degree in a quantitative field such as statistics, mathematics, economics, computer science, engineering, or a related area, or equivalent practical experience.

• Strong technical proficiency in Python or R and SQL.

• Proven experience in guiding analytical or machine learning products from an ambiguous business challenge through development, deployment, adoption, and measurable impact.

• In-depth understanding of statistical modeling, machine learning, experimentation, causal inference, and model evaluation methods.

• Capability to identify appropriate business problems to address and convert business objectives into decision, measurement, and analytical frameworks.

• Experience in influencing senior stakeholders through data and analysis and leading cross-functional projects.

• Excellent written and verbal communication skills.

• Strong judgment, ownership, and execution abilities.

• Preferred: Background in B2B SaaS, subscription models, customer lifecycle, or commercial analytics.

• Preferred: Experience in constructing or scaling decision intelligence, next-best-action, propensity, prioritization, experimentation, or other analytical products.

• Preferred: Familiarity with production machine learning and model operational lifecycle.

• Preferred: Experience managing a portfolio of analytical products.

• Preferred: Background in developing senior technical talent and enhancing organizational capabilities.

🏝️ Benefits

• Annual cash bonuses.

• Stock grants.

• Comprehensive benefits package.

• In-person onboarding and/or in-person ID verification may be required.