Senior Data II Scientist
POS-P655
Our mission at HubSpot 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.
About the job
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Senior Data II Scientist
POS-P655
Our mission at HubSpot 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.