Senior Manager, GTM Data Science

• Shape the multi-quarter Data Science roadmap for customer engagement use cases
• Partner with senior leaders across Sales, Marketing, and Customer Success to prioritize high-value decisions
• Translate strategic questions into decision frameworks, analytical problem statements, intervention strategies, success metrics, and business cases
• Advise executives and cross-functional leaders, challenge assumptions, make recommendations, and communicate tradeoffs
• Define success measures and ensure adoption and realized business outcomes
• Own and manage a portfolio of Decision Intelligence initiatives across retention, churn, growth, upsell, cross-sell, segmentation, propensity, lead prioritization, compliance, attribution, benchmarking, simulations, and next-best action
• Lead initiatives from problem formulation and data readiness through modeling, validation, deployment, workflow integration, experimentation, impact measurement, and monitoring
• Partner with program management, analytics engineering, data engineering, product managers, and federated analytics teams
• Establish operating rhythms and quality standards, including roadmap reviews, technical reviews, launch readiness, outcome reviews, and risk escalation
• Provide technical leadership across prediction, experimentation, causal inference, optimization, ranking, simulation, and related methods
• Guide 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
• Ensure machine learning products connect insights to actions and measurable incremental impact
• Stay current on advances in machine learning, AI, experimentation, causal inference, and decision intelligence
• Lead, recruit, retain, and develop a high-performing data science team
• Coach senior individual contributors and emerging leaders
• Conduct performance and talent reviews, provide feedback, identify development opportunities, and build succession and hiring plans
• Create an inclusive team environment focused on technical rigor, learning, collaboration, and accountability
• Build reusable methods, decision frameworks, operating practices, and partnerships across the EDA organization

Requirements

• 8+ years of experience in data science, machine learning, advanced analytics, or a related quantitative field, including significant hands-on applied experience
• 3+ years of experience managing data science, machine learning, or advanced analytics teams
• Advanced degree in a quantitative discipline such as statistics, mathematics, economics, computer science, engineering, or a related field, or equivalent practical experience
• Strong technical fluency in Python or R and SQL
• Experience taking analytical or machine learning products from an ambiguous business problem through development, deployment, adoption, and measurable impact
• Strong knowledge of statistical modeling, machine learning, experimentation, causal inference, and model evaluation techniques
• Ability to identify the right business problems to solve and translate business objectives into decision, measurement, and analytical frameworks
• Experience influencing senior stakeholders with data and analysis and leading cross-functional initiatives
• Excellent written and verbal communication skills
• Strong judgment, ownership, and execution
• Preferred: Experience with B2B SaaS, subscription, customer lifecycle, or commercial analytics
• Preferred: Experience building or scaling decision intelligence, next-best-action, propensity, prioritization, experimentation, or other analytical products
• Preferred: Experience with production machine learning and model operational lifecycle
• Preferred: Experience managing a portfolio of analytical products
• Preferred: Experience developing senior technical talent and organizational capability

Core Competencies

Demonstrates expertise in Data Science and Machine Learning, with a strong focus on developing and managing analytical products that drive business outcomes. Proven ability to lead cross-functional teams, influence stakeholders, and establish decision frameworks that translate strategic objectives into measurable results.

Highest-signal resume keywords

• Data Science Leadership
• Machine Learning Expertise
• Statistical Modeling
• Python or R Proficiency
• SQL Proficiency

ATS Optimization Keywords

Hard Skills

• Data Science
• Machine Learning
• Advanced Analytics
• Statistical Modeling
• Causal Inference
• Experimentation
• Model Evaluation
• Decision Frameworks
• Analytical Problem Solving
• Portfolio Management

Soft Skills

• Excellent Communication
• Strong Judgment
• Ownership
• Execution
• Coaching

Industry Keywords

• B2B SaaS
• Customer Lifecycle
• Commercial Analytics
• Decision Intelligence
• Next-Best-Action

Tools & Technologies

• Python
• R
• SQL