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Intercom

Senior GTM Data Scientist

Reposted 6 Hours Ago
Easy Apply
In-Office
San Francisco, CA, USA
198K-247K Annually
Senior level
Easy Apply
In-Office
San Francisco, CA, USA
198K-247K Annually
Senior level
The Senior GTM Data Scientist will design and deploy predictive ML systems that enhance customer acquisition, sales efficiency, and retention. Responsibilities include building models, defining product vision, and architecting data foundations, all while ensuring model impact on revenue.
The summary above was generated by AI

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?
  1. 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.

     2. 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).   

#LI-Hybrid

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.

Top Skills

Python
R
SQL
HQ

Intercom San Francisco, California, USA Office

The SF office is located in the bustling SoMa district. It's just off Market Street, a 2 minute walk from Montgomery BART and Muni. The area is dotted with amazing dining spots, although our Workplace Experience team also looks after us with tons of delicious food, drink and snacks.

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