POS-29559

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 Senior 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.
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 2+ 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

We know the confidence gap and impostor syndrome can get in the way of meeting spectacular candidates, so please don’t hesitate to apply — we’d love to hear from you.
.
At HubSpot, we value both flexibility and connection. Whether you’re a Remote employee or work from the Office, we want you to start your journey here by building strong connections with your team and peers. If you are joining our Engineering team, you will be required to attend a regional HubSpot office for in-person onboarding. If you join our broader Product team, you’ll also attend other in-person events such as your Product Group Summit and other gatherings to continue building on those connections.
If you require an accommodation due to travel limitations or other reasons, please inform your recruiter during the hiring process. We are committed to supporting candidates who may need alternative arrangements
Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
About HubSpot
HubSpot (NYSE: HUBS) is an AI-powered customer platform with all the software, integrations, and resources customers need to connect marketing, sales, and service. HubSpot’s connected platform enables businesses to grow faster by focusing on what matters most: customers.
At HubSpot, bold is our baseline. Our employees around the globe move fast, stay customer-obsessed, and win together. Our culture is grounded in four commitments: Solve for the Customer, Be Bold, Learn Fast, Align, Adapt & Go!, and Deliver with HEART. These commitments shape how we work, lead, and grow.
We’re building a company where people can do their best work. We focus on brilliant work, not badge swipes. By combining clarity, ownership, and trust, we create space for big thinking and meaningful progress. And we know that when our employees grow, our customers do too.
Recognized globally for our award-winning culture by Comparably, Glassdoor, Fortune, and more, HubSpot is headquartered in Cambridge, MA, with employees and offices around the world.

Explore more:

• HubSpot Careers
• Life at HubSpot on Instagram

By submitting your application, you agree that HubSpot may collect your personal data for recruiting, global organization planning, and related purposes. Refer to HubSpot’s Recruiting Privacy Notice for details on data processing and your rights.

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 development

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 enablemen