Data Scientist: ML for Consumer Lending | Hybrid

Lloyds Banking Group; City Of London; Hybrid; GBP 70,000 - 107,000; Full time

Job summary

A major financial institution is seeking a motivated Data Scientist to join their Consumer Lending team. The role involves building and improving Machine Learning solutions to enhance various finance products. Candidates should have a strong background in statistical modelling, SQL, and Python, along with experience in deploying machine learning models in cloud environments. The position offers a competitive salary and a hybrid working pattern.

Benefits

Extensive benefits package

Inclusive and diverse workplace

Career development opportunities

Qualifications

• Strong theoretical and applied knowledge of statistical modelling and/or ML techniques.
• Computer science fundamentals: a clear understanding of data structures and algorithms.
• Good understanding of SQL and prior experience of working with large data sets.
• Experience across the full software development lifecycle, including deployment of ML models.
• Exposure to cloud tooling (e.g. GCP) and visualisation tools (e.g. Tableau, PowerBI) is desirable.

Responsibilities

• Identify, develop and implement new solutions to deliver customer and business value.
• Run, maintain and improve Python data science models.
• Work closely with business teams to identify new use cases for Data Science.
• Promote high quality ML practices and maintain effective control environments.
• Deliver in line with data science, model governance and risk management policies.

Skills

Statistical modelling

Machine Learning techniques

SQL

Python

Docker

Kubernetes

GCP cloud tooling

Data visualization tools

Job description

A major financial institution is seeking a motivated Data Scientist to join their Consumer Lending team. The role involves building and improving Machine Learning solutions to enhance various finance products. Candidates should have a strong background in statistical modelling, SQL, and Python, along with experience in deploying machine learning models in cloud environments. The position offers a competitive salary and a hybrid working pattern.