Data Scientist - Financial Services ML & Data Pipelines

Efinancialcareers; City of Edinburgh, Reading; On-site; AUD 175,000 - 253,000; Full time

Benefits offered by this job

Pension up to 18%

Share Save and Share Incentive Plan

38 days annual leave

Time Off When You Need It

Inspiring Families policy

Private Healthcare

Critical Illness cover

Life Assurance

Job summary

M&G is seeking an experienced data scientist to design, build, and optimise data solutions for actuarial modelling and assumption setting. You will lead scalable data workflows, apply ML techniques, ensure governance, and guide junior team members while delivering high-quality, auditable outputs.

The role emphasizes collaboration with stakeholders, strong documentation, and continuous improvement of data platforms within a heavily regulated financial services environment.

Qualifications

• Experience applying data science techniques to financial services.
• Experience building and maintaining large data pipelines with high data quality.
• Ability to translate business problems into measurable data science solutions.
• Experience in audited environments with controls and documentation.

Responsibilities

• Design, build, and maintain scalable data pipelines to transform data for actuarial modelling.
• Ensure data quality, integrity, and governance across pipelines.
• Collaborate with stakeholders to translate requirements into technical solutions.
• Optimise data systems for performance, reliability, and scalability.
• Provide technical guidance on data science approaches and best practices.
• Integrate multiple data sources to create cohesive datasets.
• Contribute to continuous improvement of data platforms and engineering standards.

Skills

Data science techniques

Azure Databricks

Spark

Data governance

Stakeholder engagement

Communication

People management

Tools

Python

Spark SQL

SQL

Job description

M&G is seeking an experienced data scientist to design, build, and optimise data solutions for actuarial modelling and assumption setting. You will lead scalable data workflows, apply ML techniques, ensure governance, and guide junior team members while delivering high-quality, auditable outputs.

The role emphasizes collaboration with stakeholders, strong documentation, and continuous improvement of data platforms within a heavily regulated financial services environment.