Design and evaluate AI systems including chatbots and multi-agent workflows, leading end-to-end delivery of high-visibility projects and collaborating closely with engineers and product stakeholders.
Company overview
Consumer Edge (“CE”) delivers real-time transaction-based intelligence enriched by AI and deep industry expertise. Our mission is to turn complex consumer and business data into actionable insights. Our technology team is distributed across Europe and the US and is driven by curiosity and rigor.
Role summary
As a Staff Data Scientist on the AI Products team, you’ll design, evaluate & deliver AI systems including chatbots, RAG frameworks, and multi-agent workflows. You will lead end to end delivery of highly visible projects within the team, partnering closely with engineers and product stakeholders to take ideas from exploration through production.
Your main responsibilities
We’re looking for someone with
Tech stack & team context
Part of the AI Products group alongside engineers and scientists across Dublin, Italy, and New York. The stack includes Python, Vertex AI, BigQuery, Dataflow, and Hugging Face libraries. The team operates with high autonomy and values rapid experimentation balanced with scientific discipline.
Benefits & perks
We are a remote-first company with a distributed environment and flexible working arrangements. We believe that distributed workers should be first-class citizens. We also have an office in New York if offices are your thing
Remote-Friendly
We are a remote-first company with a distributed environment and flexible working arrangements.
Consumer Edge specializes in consumer data analytics, providing investment firms and global brands with deep insights into consumer spending patterns. Our platform empowers businesses to make informed decisions by harnessing the power of data, setting us apart in the competitive analytics landscape.
Understand the required skills and qualifications, anticipate the questions you may be asked, and study well-prepared answers using our sample responses.
Staff Data Scientist Q&A's