Data Scientist
London, UK
Hybrid
The Company
Our client is an innovative startup with dual headquarters in the UK and US, pioneering the future of data protection. Their mission is to help organisations leverage the potential of generative AI without sacrificing security or privacy. With a commitment to cutting-edge solutions, they are shaping a secure AI-powered future that empowers enterprise clients to use AI responsibly.
Job Description
As a Data Scientist on this team, you’ll play a key role in advancing secure generative AI practices by building and curating datasets that underpin high-performing models. In this role, you’ll:
Collaborate to design and develop comprehensive datasets for training and fine-tuning models that detect sensitive data.
Apply a high level of precision to ensure data accuracy and integrity, forming the foundation of reliable models.
Keep up with the latest data science trends, consistently seeking ways to optimise dataset creation and boost model effectiveness.
Work closely with engineering and security teams, facilitating smooth integration with advanced security solutions.
Your contributions will directly impact the development of technology that supports secure generative AI adoption in enterprise environments.
Requirements
Ideal Qualifications:
Demonstrated experience managing models in production, integrated into live products.
A strong track record in building and managing high-quality datasets.
A product-focused mindset, geared toward continuous, incremental improvement.
Advanced proficiency in Python and familiarity with essential libraries.
Knowledge of natural language processing (NLP) techniques.
Strong communication and collaboration skills.
Preferred Qualifications:
Experience with generative AI models or large language models (LLMs).
Background in the data security domain.
Understanding of classification methods and data categorization techniques.
Experience in customer-facing roles to gain a deeper understanding of the problem domain.
Familiarity with cloud platforms such as AWS, Azure, or GCP.