Pricing Data Scientist — ML for Insurance Analytics

hastingsdirect; Leicester; Hybrid; GBP 55,000 - 90,000; Full time

Benefits offered by this job

Flexible hybrid working

Annual bonus

Pension

Life assurance

Healthcare

Cycle to work

Wellbeing programs

Job summary

Hastings Direct, a digital insurance provider, seeks a Data Scientist in a hybrid role based in the UK to design, deploy and refine predictive pricing models. You will work within a team championing ML techniques to improve predictive performance on large datasets and translate model outputs into pricing strategies.

You will collaborate with pricing teams and deliver automated pipelines, using cloud platforms and modern data tools, while adhering to governance and responsible AI practices.

Qualifications

• Connect data, analytics and ML models to business outcomes.

Responsibilities

• Build, develop and enhance models in the Market Pricing team to improve competitive positioning
• Create and maintain tools to support modelling activities
• Investigate and incorporate powerful new rating factors
• Collaborate with pricing teams to translate model outputs into actionable pricing strategies
• Build, improve and maintain data science and machine learning workflows used within Market Pricing
• Investigate issues across data, model and pipeline workflows
• Automate manual steps where this improves quality, speed or control
• Apply good engineering practices, including Git, code review, testing and documentation

Skills

Data science

ML models

Cloud platforms

Big data tools

Linux CLI

Git & testing

Code pipelines

Explainability

Pricing/insurance

Tools

Snowflake

Databricks

Spark

Job description

Hastings Direct, a digital insurance provider, seeks a Data Scientist in a hybrid role based in the UK to design, deploy and refine predictive pricing models. You will work within a team championing ML techniques to improve predictive performance on large datasets and translate model outputs into pricing strategies.

You will collaborate with pricing teams and deliver automated pipelines, using cloud platforms and modern data tools, while adhering to governance and responsible AI practices.