Senior Manager, GTM Data Science
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Job Description
Senior Manager leading Autodesk’s GTM data science portfolio for Sales, Marketing, and Customer Success. Building machine learning products that improve customer retention, growth, and engagement decisions.
Responsibilities:
- 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
Benefits:
- Annual cash bonuses
- Stock grants
- Comprehensive benefits package
- In-person onboarding and/or in-person ID verification may be required
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