About the job
Intercom is a pioneering AI Customer Service company dedicated to empowering businesses to deliver exceptional customer experiences.
Our advanced AI agent, Fin, stands as the premier customer service AI solution available, enabling businesses to provide round-the-clock, flawless customer support while significantly enhancing overall customer satisfaction. When integrated with our Helpdesk, it forms a comprehensive solution known as the Intercom Customer Service Suite, which offers AI-driven assistance for more intricate or high-touch inquiries requiring human interaction.
Founded in 2011 and trusted by nearly 30,000 businesses worldwide, Intercom is redefining the benchmarks for customer service. By adhering to our core values, we continuously challenge conventions, build with agility and urgency, and consistently deliver exceptional value to our clients.
What is the opportunity?
The AI Group at Intercom is tasked with defining innovative machine learning features, researching suitable algorithms and technologies, and quickly deploying prototypes for our customers.
We are highly product-oriented. Our team, consisting of over 50 ML scientists, engineers, designers, and researchers, collaborates closely with various departments across the organization. We prioritize rapid production cycles, often transitioning to beta testing within weeks following successful offline evaluations.
We continually conduct experiments and measure the effectiveness of our AI features, employing both frequentist and Bayesian methodologies, creating dashboards for result tracking, and delving deeply into user interactions to understand success metrics amidst the complexities of stochastic AI products.
We are seeking a passionate Analytics Engineer to join our AI Group and contribute to our ongoing efforts.
What will I be doing?
- Data Platform Development: Design, develop, and oversee scalable data pipelines and ETL processes to establish a robust, analytics-ready data infrastructure.
- Cross-functional Collaboration: Collaborate with AI analysts, ML scientists, engineers, and business teams to comprehend data requirements and ensure the delivery of accurate, reliable, and user-friendly data solutions.
- Data Strategy & Governance: Drive initiatives in data modeling, ownership of data quality, management of warehouses, and production support for key operational workflows.
- Advanced Analytics & Insights: Perform data analysis and develop custom models to inform strategic business decisions and measure performance.
- Automation & Optimization: Enhance the efficiency of data collection and reporting processes.

