Applied Scientist, Lloyds

• We are seeking a candidate with a genuine passion in the field of Deep Learning with particular expertise in building large scale Deep Learning solutions
• Experience building, deploying and maintaining advanced Machine Learning models
• Well versed in the scientific Python ecosystem (NumPy, Scikit-Learn, Pandas etc.)
• Strong Data Engineering underpinnings and an ability to work with big data (Tbs)
• Experience in at least one Deep Learning framework (PyTorch, TensorFlow, JAX etc)
• Strong leadership skills, using empathy, clarity and challenge to support your team to be their best
• Strong communication skills with an ability to adapt style for different audiences

Desirable

• We are looking to recruit an Applied Scientist to sit within a newly formed AI Innovation team. This role will be fundamental in supporting the platform in integrating pioneering machine learning technology to prevent fraud and financial crime
• The AI Innovation team will be responsible for pioneering our next wave of fraud and financial crime machine learning models. Think Deep Learning auto regressive models on Tbs of transaction data or innovating on our current anti-money laundering approaches using graphical neural networks/deep anomaly detection models
• Using your skills to create ML models with an economic crime focus, pushing the boundary of what is currently possible by embracing innovative new approaches
• Leading small teams in the development and maintenance of AI products that serve internal and external customers
• Working with diverse datasets and efficiently process and learn from them in order to gain insights
• Engaging with data engineering teams within the Economic Crime Intelligence lab to help guide how we can best make use of our ECP data
• Collaborating with collaborators to understand business problems and help guide where data AI solutions could prove fruitful

• End Date: June 3, 2025