Senior Data Scientist

About Cadensys

Cadensys is founded by ex-Revolut and Trade Republic executives and backed by leading global VCs. We are on a mission to revolutionise the way businesses are operated. Cadensys solves the problems caused by scattered tools and disjointed workflows by unifying data and coordinating agents.

We are building an operating system orchestrating work between human workers and AI agents, across all tools and company-wide. By learning how humans make decisions and take actions, we enhance their effectiveness by allowing them to be problem solvers and not tool operators.

We are looking for a Data Scientist committed to driving change in the way people work and with a desire to innovate by creating data-driven AI-solutions supporting process mining, mapping, monitoring and design.

Role Overview

As a Data Scientist, you will play a key role in developing cutting-edge AI solutions, designing and implementing systems that integrate AI into real-world business applications. This includes focusing on agentic applications for information and data retrieval, summarization, process mining, and automation. You will also develop and refine quantitative frameworks and methodologies while exploring the intersection of Cadendys' Orchestrator and generative AI products. This involves evaluating different product integrations, such as embedding AI capabilities into internal portals or third-party B2B SaaS platforms like Jira. Additionally, you'll analyze how various data types—unstructured documents, structured datasets, and external sources—can be effectively combined. You will also study knowledge workers in specialized fields like engineering and support, considering how to best empower Cadendys' customers to harness the growing ecosystem of AI agents for maximum value.

Key Responsibilities

• Development AI solutions to automate business processes, ensuring high performance, scalability, and reliability.
• Build advanced agentic LLM/RAG systems, optimising performance and cost, making decisions on mixing and matching foundation, fine-tuned, and home-build models to achieve best-in-class performance of the product.
• Work with product engineering teams to understand business requirements and translate them into AI-powered solutions.

Requirements

• Strong expertise in Python, SQL and the modern data stack (e.g. dbt pipelines for ETL/ELT).
• Experience in deep learning with natural language processing.
• Strong understanding of large language models and grounding techniques.
• Experience deploying and monitoring AI models in production and at scale.
• Strong knowledge of data science in general.
• Good product thinking skills to design and implement complex AI algorithms solving business problems.
• Excellent communication and collaboration skills to partner with in-house product teams and clients.

Nice to have

• A master's or PhD degree in a quantitative discipline.
• Experience with knowledge graph / ontology construction from structured and unstructured data and its use for information retrieval.
• Experience interfacing with disparate remote sources of structured and unstructured data (API, data warehouse, and file based).