Lead Data Scientist

POS-30411

HubSpot’s mission is to help millions of companies Grow Better. We believe AI will dramatically accelerate our Go-to-Market (GTM) teams and their ability to effectively expand our customer base and serve existing customers. We’re seeking a talented, experienced Lead Data Scientist to join our Data & Systems Intelligence (DSI) team to support internal clients through the delivery of scalable AI/ML products and create leverage for the business.

This role will sit on the Customer Success Data Science & AI team. Your role will focus on extract insights from our data and developing how we develop and store recommendations for HubSpot’s customers. The delivery mechanism for these insights can range from digital agentic workflows, to marketing emails, and even face to face contact. This role heavily uses both structured and unstructured data, and would leverage both predictive and generative AI. We’re looking for someone who can leverage a broad range of technical skills to build and deploy models, and apply soft skills to drive strategy on how we help our customers grow better!

You will be joining a high-growth, high-powered team of Data Scientists, ML Engineers, and Analytic Engineers that deeply values intellectual curiosity, collaboration, and autonomy. You will have an enormous impact in a rapidly growing space–we’ve got big plans and want talented, passionate data scientists to help us achieve them. Successful candidates will need to work with stakeholders to deeply understand their business problems, creatively design solutions, and lead the timely execution of the chosen plan.

Objectives of this Role

• 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

Role Responsibilities and Duties

• 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

Skills and Qualifications

• 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

Preferred Qualifications

• Background in econometrics, operations research, or quantitative marketing with application to B2B SaaS metrics
• Experience using a deep learning Python framework (Tensorflow, pytorch, etc)
• Prior experience supporting GTM teams or functions, especially in B2B SaaS companies
• 2+ years of experience leading GAI initiatives independently
• Experience building and deploying LLM agents
• Experience building natural language processing (NLP) models