Forward Deployed Data Scientist

Intercom•San Francisco, CA

31d•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? The Research, Analytics & Data Science (RAD) team at Intercom uses data and insights to drive evidence-based decision-making. We're a team of data scientists and product researchers who use data - both big and small - to unlock actionable insights about our customers, our products and our business. We generate insights that build customer empathy, drive product strategy and shape products that deliver real value to our customers. We're now seeing strong demand for data scientists who can apply their expertise directly with our most strategic customers. As a Forward Deployed Data Scientist, you'll embed with customers to build Enterprise-grade Fin deployments. You'll play a pivotal role in transforming how our most strategic customers scale customer support - working closely with them and our go-to-market teams to design, build, and implement data-driven solutions that unlock measurable impact. You'll also feed insights from these frontline deployments back into Intercom's product and strategy - helping shape the future of AI customer service. This is a high-ownership role for someone who thrives in ambiguous environments, is energized by solving complex, real-world problems with data, and is motivated by seeing their work translate into both customer impact and product evolution.

Requirements

Proven ability to apply data science in real-world business contexts to drive measurable outcomes.
Strong collaboration mindset; skilled at working across Sales, Success, Product, and Engineering.
High adaptability and ownership: able to shift between deep technical analysis and high-level strategic framing.
Excellent communication skills, both technical and non-technical.
Rapidly prototype bespoke solutions for customers - knowing when lightweight analysis is sufficient versus when to scale.
Excellent SQL skills and fluency in Python/R, with experience applying analytical and statistical methods to business problems.
Experience with AI/ML evaluation, LLM-driven applications, or conversational AI.
Willing to travel and work on-site with customers to build deep relationships and uncover insights firsthand.

Nice To Haves

Experience in technical consulting, customer-facing analytics, or SaaS product data science.
Experience applying AI to scale the data science workflow.

Responsibilities

Drive the adoption of Fin by helping customers automate and scale their support operations.
Embed with strategic customers to understand their support workflows, data, and business challenges - to identify and implement opportunities where AI can deliver measurable impact.
Steer customers toward best practices in measurement and AI adoption to realize the full value of Fin.
Partner closely with Sales, Success, and Product to deliver seamless customer experiences and successful deployments, and to create feedback loops that shape product development.
Use AI to prototype, test, and scale data-driven solutions, building tools that make us faster and more effective in driving Fin adoption and customer impact.