# Senior GTM Data Scientist

**Company**: Intercom
**Location**: San Francisco, California
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $197,600 - $246,713
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/intercom/jobs/7652268
**Canonical**: https://yubhub.co/jobs/job_27ecbf0a-523

## Description

We are 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, sales efficiency, and customer retention and expansion.

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.

### What will I be doing?

- 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)

You don’t just build models - you ensure they change behavior.

### 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

You operate as a mini GM for your data products.

### 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

You raise the technical bar for the GTM organization.

### What impact might I have?

Within 6-12 months, you might:

- Launch predictive models that materially improve conversion, expansion, or retention

- Reduce inefficiencies in Sales workflows through automation

- Help leadership make investment decisions backed by rigorous data science

- Influence GTM strategy through quantitative insight and modeling

Success is measured in business outcomes - not dashboards built.

## Skills

### Required
- Expert-level SQL
- Advanced Python or R for modeling and experimentation
- Strong foundation in statistics and experimental design
- Predictive modeling
- Feature engineering

### Nice to have
- Causal inference or uplift modeling
- Model deployment & monitoring