Python Engineer – Inside IR35 – Hybrid role
We are looking for an experienced Python Engineer to join the Fraud Team at a large retail bank. As part of this team, you will be responsible for designing and implementing solutions to detect, prevent, and analyse fraudulent activities. You will be working with large datasets and building machine learning models, algorithms, and tools using Python. In addition, you will also need to work with SQL databases, as a key skill for this role.
- Work on the design and development of Python-based machine learning models and algorithms to detect, prevent, and analyze fraudulent activities.
- Analyze large datasets to identify fraudulent patterns and trends, and work with the fraud analysts and investigators to improve the bank’s fraud detection capabilities.
- Develop Python-based tools and scripts to automate data processing, model training, and other aspects of the fraud prevention process.
- Integrate machine learning models and algorithms into the bank’s fraud prevention systems and monitoring their performance to ensure they are accurate and effective.
- Collaborate with data scientists and other members of the data analytics team to integrate machine learning models into larger data pipelines and analytics workflows.
- Work with SQL databases to access and manipulate large datasets, create and execute complex queries, and ensure data integrity and consistency.
Qualifications and Skills:
- Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
- Strong programming skills in Python and related libraries such as NumPy, pandas, and Scikit-learn.
- Experience with SQL databases and data visualization tools such as Tableau.
- Experience with machine learning frameworks such as TensorFlow, Keras, and PyTorch.
- Strong problem-solving and analytical skills, with the ability to work in a fast-paced environment.
- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.