Senior Manager, GTM Data Science

Stellenbeschreibung:

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.