Lead Data Scientist

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6 hours ago

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HubSpot

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B2B • SaaS • Marketing

HubSpot is an AI-powered customer platform that combines marketing, sales, and customer service software into one integrated suite. With over 238,000 customers in 135 countries, HubSpot offers tools for marketing automation, sales management, customer service, content marketing, operations, and B2B commerce. With products like Marketing Hub, Sales Hub, Service Hub, and Content Hub, HubSpot enables businesses to generate leads, close deals, and provide excellent customer support, all while using AI to enhance operations and insights. The platform is designed to unify teams and customer data, supporting both small startups and large enterprises in their growth journey.

1001 - 5000 employees

Founded 2006

🤝 B2B

☁️ SaaS

📋 Description

• Design, build, and deploy sophisticated machine learning systems that directly optimize for measurable business outcomes across go-to-market functions • Identify and mature data sources that will further data science at HubSpot • Build strong relationships with internal stakeholders, develop a deep understanding of their business problems, and act as a trusted advisor for ML/AI solutions • Use data to inform key business decisions and communicate findings effectively with senior leadership • Experiment with Generative AI (LLM/RAG) as potential business accelerants • Keep current with technical and industry developments • Partner with stakeholders and cross-functional teams to identify business problems, scope technical solutions, and build execution plans in a consultative manner • Lead the design, prototyping, and deployment of ML models and intelligence products in an iterative, feedback-driven development cycle • Apply a broad range of machine learning techniques—including classical, deep learning, GenAI, and agent-based methods—to solve diverse business problems • Design and execute analytical experiments to validate hypotheses, test strategies, and uncover new business opportunities • Identify causes of business outcomes, and amplify positive results through the intervention of our deployed systems • Collaborate with engineers to implement models and intelligence systems in a scalable, maintainable, and production-ready manner • Extract, clean, and structure data from both structured and unstructured sources to support modeling and analysis • Champion adoption and usage of data and AI products through clear communication and stakeholder enablement

🎯 Requirements

• 5+ years experience in data science with multiple ML models deployed and affecting real business outcomes, or 3+ years experience with quantitative Masters or PhD. • Expert level knowledge in Python and SQL (experience with DBT a plus) • Proficient using version controls systems (git, ideally) • Experience with A/B testing frameworks, causal inference methods, and experimental design to measure incremental business impact • Proven track record of building sophisticated predictive models (e.g. churn prediction, lead scoring, customer lifetime value, propensity modeling) that demonstrably improved go-to-market metrics • Experience prompt engineering, working with, and evaluating Gen AI systems • Ability to effectively communicate with non-technical audiences, and using data to persuasively present to senior management to inform strategic decision making.