Applied Data Scientist - RAG / MCP / Gen AI

Responsibilities:

• Collaborate directly with clients and with the client's Europe-based engineering team to understand business needs and translate them into data-driven solutions.
• Own end-to-end model development: data exploration, prototyping, validation, deployment, and monitoring.
• Enhance and extend existing predictive and generative AI offerings for our financial services client, including forecasting models for financial data and customer support prediction.
• Contribute to generative AI solutions such as RAG pipelines and MCP servers, integrating them into production workflows.
• Deploy and maintain solutions across public cloud (AWS) and private/on-premise cloud environments.
• Present findings, actionable insights, and recommendations to both technical and non-technical stakeholders.
• Stay current with the latest advancements in AI and data science to continuously enhance our offering.

Requirements:

• 3-5 years of hands-on experience in data science, including customer-facing roles.
• Proven track record in building and deploying predictive models; experience with generative AI (RAG, LLM-based solutions, MCP servers) is a strong plus.
• Experience with forecasting and time-series modelling, ideally on financial or other structured business data.
• Proficiency in Python and SQL; experience with cloud platforms (AWS and/or GCP) is desirable, including deployment in both public and private/on-premise environments.