Pricing Data Scientist: Build & Deploy ML Models

Harnham; Manchester; On-site; GBP 60,000 - 90,000; Full time

Job summary

Harnham is seeking a Data Scientist to join a growing insurance data science team, tackling complex pricing challenges, building production-ready models, and delivering insights that directly affect commercial outcomes.

You will work with Python, SQL, Databricks and PySpark to analyse large datasets, own projects from problem definition through deployment, and present findings to both technical and non-technical stakeholders. Experience in insurance or regulated environments is advantageous.

Qualifications

• Strong commercial Data Science experience.
• Advanced Python and SQL skills.
• Experience with Databricks and PySpark.
• Knowledge of ML techniques such as XGBoost and LightGBM.
• Strong statistical modelling capability.
• Excellent problem-solving and stakeholder management skills.
• Experience in insurance, financial services, or another regulated environment is advantageous.

Responsibilities

• Build, validate and deploy machine learning and statistical models.
• Work with Python, SQL, Databricks and PySpark to analyse large datasets.
• Solve pricing and risk-related business challenges.
• Explore new data sources and test innovative ideas.
• Own projects from problem definition through to implementation.
• Present insights to technical and non-technical stakeholders.
• Support and mentor junior Data Scientists.

Skills

Advanced Python

SQL

XGBoost

LightGBM

Statistical Modelling

Stakeholder Management

Pricing domain knowledge

Insurance knowledge

Problem solving

Tools

Databricks

PySpark

Job description

Harnham is seeking a Data Scientist to join a growing insurance data science team, tackling complex pricing challenges, building production-ready models, and delivering insights that directly affect commercial outcomes.

You will work with Python, SQL, Databricks and PySpark to analyse large datasets, own projects from problem definition through deployment, and present findings to both technical and non-technical stakeholders. Experience in insurance or regulated environments is advantageous.