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Salary: USD 206,600 - 229,000 / annual
Fin (now part of Salesforce) is building the highest-performing AI Customer Agent on the market, enabling businesses to deliver impeccable, always-on customer support across service, sales, and ecommerce. The Research, Analytics & Data Science (RAD) team uses data and insights to drive evidence-based decision-making across the organization.
As a Forward Deployed Data Scientist, you will embed with strategic customers to build enterprise-grade Fin deployments and transform how they scale customer support. This is a high-ownership role combining technical depth with customer-facing impact. You will work closely with customers and go-to-market teams to design, build, and implement data-driven solutions that unlock measurable impact. You'll also feed insights from frontline deployments back into Intercom's product and strategy, helping shape the future of AI customer service.
Key responsibilities include:
- Drive Fin adoption by helping customers automate and scale their support operations
- Embed with strategic customers to understand their support workflows, data, and business challenges, identifying where AI can deliver measurable impact
- Steer customers toward best practices in measurement and AI adoption to realize full value from Fin
- Partner closely with Sales, Success, and Product to deliver seamless customer experiences and successful deployments, creating feedback loops that shape product development
- Use AI to prototype, test, and scale data-driven solutions, building tools that accelerate Fin adoption and customer impact
- Travel and work on-site with customers to build deep relationships and uncover insights firsthand
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
- Rapid prototyping with systems thinking; ability to determine when customers need fast, bespoke answers versus scalable solutions
- Excellent SQL and production-aware Python; write code others can run and apply analytical and statistical methods to real business problems
- Experience with AI/ML evaluation, LLM-driven applications, or conversational AI
- Willing to travel and work on-site with customers
Bonus skills:
- Experience in technical consulting, customer-facing analytics, or SaaS product data science
- Experience reframing problems, not just solving them; ability to identify when the initial question isn't the right one
- Experience applying AI to scale the data science workflow
