Senior GTM Data Scientist

Intercom•San Francisco, CA

2h•Hybrid

About The Position

Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences. Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent. Founded in 2011 and trusted by nearly 30,000 global businesses, Intercom is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers. What's the opportunity? Intercom is building a GTM Data Products team to embed machine learning and AI directly into our Sales and Marketing workflows. We are hiring a Senior GTM Data Scientist to design and deploy predictive systems that materially improve: Customer acquisition (e.g. via lead scoring, attribution) Sales efficiency (e.g. via book carves, sales quotas) Customer retention and expansion (e.g. via revenue prediction) This is not a reporting role. This role owns end-to-end data products - from problem framing and modeling to deployment and operational integration - that directly influence how our GTM organization prioritizes leads, manages accounts, allocates resources, and drives revenue. You’ll work closely with Marketing, Sales, and RevOps leadership to build ML-powered systems that change how decisions are made at scale. If you are excited about building applied machine learning systems that generate measurable revenue impact, this role is for you.

Requirements

5+ years in Data Science, Applied ML, or Advanced Analytics
Experience building predictive models deployed into production environments
Experience working with Sales, Marketing, or GTM teams in a B2B SaaS environment preferred
Proven track record influencing senior stakeholders through data
Expert-level SQL
Advanced Python or R for modeling and experimentation
Strong foundation in statistics and experimental design
Predictive modeling
Feature engineering
Model evaluation & validation

Nice To Haves

Causal inference or uplift modeling (strong plus)
Model deployment & monitoring (strong plus)

Responsibilities

Build Revenue-Impacting ML Systems
Develop, deploy, optimize predictive models (lead scoring, account prioritization, marketing attribution, revenue estimation)
Productionize models into operational systems (Salesforce, Marketo, outbound workflows)
Monitor model performance and iterate for measurable business lift
Design and implement experimentation frameworks (A/B testing, holdouts, incremental lift measurement)
Apply advanced techniques when appropriate (e.g., causal inference, uplift modeling, segmentation, LTV modeling)
Own End-to-End Data Products
Translate ambiguous business problems into clear, measurable objectives
Define GTM data products vision, success metrics, and roadmap
Ensure integration into existing workflows and systems
Lead stakeholder alignment and change management
Secure buy-in from system owners before replacing or enhancing existing solutions
Architect Scalable Data Foundations
Design robust data pipelines and modeling infrastructure in collaboration with Data Engineering / Data Infrastructure
Ensure data quality, governance, and reproducibility
Elevate the team’s standards for experimentation, documentation, and knowledge sharing
Push adoption of new tools and AI capabilities where appropriate