Job Highlights
AI-extracted key information
The Senior GTM Data Scientist at Intercom is responsible for designing and deploying predictive systems that enhance customer acquisition, sales efficiency, and customer retention. This role involves building machine learning-powered data products that directly influence the go-to-market organization and requires collaboration with various leadership teams.
Salary Range
$198k - $247k/year
Experience Level
Senior Level
Senior GTM Data Scientist
Posted 2 days ago
Full-Time
Employment Type
Remote
Work Location
$197,600 - $246,713
per year
About This Role
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.
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.
3
. 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.
What we’re looking for
Experience
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
Technical Skills
Expert-level SQL
Advanced Python or R for modeling and experimentation
Strong foundation in statistics and experimental design
Experience With
Predictive modeling
Feature engineering
Model evaluation & validation
Causal inference or uplift modeling (strong plus)
Model deployment & monitoring (strong plus)
Mindset & Leadership
You Are
A trusted advisor who influences strategy, not just execution
Deeply curious about the “why” behind business metrics
Comfortable operating with autonomy in ambiguous environments
AI-first: you look for opportunities to automate, optimize, and scale
Clear and compelling in communication - you turn complex models into strategic decisions
Impact-oriented: you prioritize work that moves revenue
Benefits
We are a well-treated bunch with awesome benefits! If there’s something important to you that’s not on this list, talk to us! :)
Competitive salary and meaningful equity
Comprehensive medical, dental, and vision coverage
Regular compensation reviews - great work is rewarded!
Flexible paid time off policy
Paid Parental Leave Program
401k plan & match
In-office bicycle storage
Fun events for Intercomrades, friends, and family!
*Proof of eligibility to work in the United States is required
The base salary range for candidates within the San Francisco Bay Area is $197,600 - $246,713. Actual base pay will depend on a variety of factors such as education, skills, experience, location, etc. The base pay range is subject to change and may be modified in the future. All regular employees may also be eligible for the corporate bonus program or a sales incentive (target included in OTE) as well as stock in the form of Restricted Stock Units (RSUs).
Policies
Intercom has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.
We have a radically open and accepting culture at Intercom. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our
core values
.
Intercom values diversity and is committed to a policy of Equal Employment Opportunity. Intercom will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.
Compensation
$197,600 - $246,713
Annual salary
Ready to Apply?
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