About the role
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-premises 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 offerings.
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 modeling, 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
- Excellent communication skills and the ability to explain complex concepts clearly, including when collaborating with distributed, cross-geography engineering teams.
- Bachelor's or master's degree in data science, computer science, statistics, or a related field.