POS-P655

Our mission at Hub Spot is to help millions of organizations grow better. On the Data & Systems Intelligence team, you’ll turn complex, ambiguous data into clear, actionable insights that directly shape how we acquire, support and grow our customers.

As a Senior II Data Scientist, you’ll operate with a high degree of autonomy and ownership, partnering closely with Customer Success and Sales leadership to solve some of the business’s most impactful problems. This is a senior individual contributor role where you are trusted to define problems, choose the right analytical approach, and drive work end to end — from exploration through execution — with meaningful influence on strategy and outcomes.

What You’ll Do

• Own complex, high-impact data science problems end to end, from framing ambiguous business questions through delivering actionable recommendations.

• Partner directly with CS and Sales leadership to influence strategy using advanced analytics, experimentation, and machine learning.

• Design, build, and deploy sophisticated models (e.g., forecasting, churn prediction, segmentation, causal inference) that drive measurable business impact.

• Lead exploratory analyses to identify risks, opportunities, and growth drivers across customer, revenue, and operational data.

• Decide independently on appropriate methodologies, tools, and trade-offs, balancing speed, rigor, and long-term scalability.

• Communicate insights and recommendations clearly to senior stakeholders through compelling, data-driven storytelling.

• Set and uphold a high bar for analytical quality, reproducibility, and technical rigor, leveraging AI-assisted workflows where they add value.

• Drive the application of GAI/LLMs into different rep-facing and customer-facing workflows.

• Act as a technical and analytical mentor, raising the bar for other data scientists and analysts through feedback, guidance, and example.

What You’ll Bring

• Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, Engineering, or a related discipline, or equivalent practical experience.

• 5+ years of professional experience working in data science, machine learning, GAI, applied statistics, or a related quantitative role.

• Strong proficiency in Python, SQL, and modern data science workflows.

• Demonstrated experience applying statistical, machine learning, and GAI techniques to real-world business problems.

• Experience deploying and monitoring models or AI products in production environments or automated decision-making workflows.

• Proven ability to work autonomously, owning problem definition, execution, and outcomes with minimal oversight.

• Experience influencing senior stakeholders through clear communication, strong judgment, and data-backed recommendations.

• Comfort operating in ambiguity, with a strong sense of accountability and ownership for results.

Nice-to-Have Qualifications

• Master’s or PhD in a quantitative field (e.g., Data Science, Statistics, Computer Science, Economics, or related).

• Experience supporting go-to-market, Sales, or Customer Success teams in a SaaS environment.

• Experience developing AI-agents, or advanced modelling techniques to scale impact.

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.

If you need accommodations or assistance due to a disability, please reach out to us using this form.

At Hub Spot, 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 Hub Spot 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.

Germany Applicants: (m/f/d) - link to Hub Spot's Career Diversity page here.

India Applicants: link to Hub Spot India's equal opportunity policy here.

About Hub Spot

Hub Spot (NYSE: HUBS) is an AI-powered customer platform with all the software, integrations, and resources customers need to connect marketing, sales, and service. Hub Spot's connected platform enables businesses to grow faster by focusing on what matters most: customers.

At Hub Spot, 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, Hub Spot is headquartered in Cambridge, MA, with employees and offices around the world.

Explore more:

• Hub Spot Careers

• Life at Hub Spot on Instagram

Hub Spot may use AI to help screen or assess candidates, but all hiring decisions are always human. More information can be found here. By submitting your application, you agree that Hub Spot may collect your personal data for recruiting, global organization planning, and related purposes. Refer to Hub Spot's Recruiting Privacy Notice for details on data processing and your rights.