Production ML Engineer for Insurance Analytics

Michael Page (UK); City Of London; On-site; GBP 75,000 - 100,000; Full time

Job summary

A prominent recruitment firm in London is seeking a Machine Learning Engineer to design and develop advanced models in the insurance industry. The ideal candidate will have strong programming skills in Python, expertise in machine learning techniques, and experience in data-intensive environments. This position offers a competitive salary between £75,000 and £100,000 per annum, along with a comprehensive benefits package and an opportunity to work on impactful projects in a collaborative setting.

Benefits

Competitive salary

Comprehensive benefits package

Opportunity to work on innovative projects

Collaborative work environment

Qualifications

• Proven expertise in machine learning techniques and tools.
• Strong programming skills in Python or similar languages.
• Experience working in data-intensive environments, particularly in the insurance industry.
• Knowledge of deploying machine learning models in production systems.
• A solid understanding of data analytics and statistical methods.

Responsibilities

• Design and develop machine learning models for business challenges in insurance.
• Collaborate to identify opportunities for data-driven solutions.
• Deploy machine learning algorithms into production environments.
• Optimise model performance for large data sets.
• Analyse data to provide actionable insights.

Skills

Machine learning techniques and tools

Programming in Python

Data analytics and statistical methods

Problem-solving skills

Job description

A prominent recruitment firm in London is seeking a Machine Learning Engineer to design and develop advanced models in the insurance industry. The ideal candidate will have strong programming skills in Python, expertise in machine learning techniques, and experience in data-intensive environments. This position offers a competitive salary between £75,000 and £100,000 per annum, along with a comprehensive benefits package and an opportunity to work on impactful projects in a collaborative setting.