Senior Data Scientist

Primary Details

Time Type:
Full time. Worker Type:
Employee.

Location:

London. Employment:
Permanent (Hybrid).

At QBE, we get to the heart of what matters for our customers. We’re an international insurer with more than 13,000 people working across 26 countries – which means we’re big enough for your ambitions, yet small enough for you to make a real impact. It’s an exciting time. We’re building momentum towards our vision to become the most consistent and innovative risk partner.

We are committed to creating a positive impact at work and in the world. As part of the QBE team, you’ll spend every day working with people who are passionate, talented and kind. You must have the right to work in the UK; sponsorship may be considered at the insurer’s discretion.

As a Senior Data Scientist, you’ll play a key role in a high‑impact pricing and data science team within a leading commercial insurer. You’ll bring solid technical expertise, deep commercial awareness, and the ability to lead analytical work that drives decision‑making across the insurance value chain. You’ll act as a point of referral for the wider team, mentor junior data scientists, and help shape best practices in model development, governance, and responsible AI.

This is ideal for someone ready to step into broader ownership, increased autonomy, and higher levels of cross‑functional influence. You will report into the Data Science Manager and apply data science and machine learning to real‑world challenges, turning complex data into clear, commercially meaningful insights.

• Deliver high‑quality, commercially impactful analytics, ML, and AI solutions.
• Lead multi‑stakeholder analytical projects across underwriting, claims, operations, and customer functions; set structure, cadence, and deliverables.
• Act as a technical point of referral for Data Scientists advising on modelling approaches, data quality, coding standards, and solution design.
• Demonstrate specialist knowledge (e.g., pricing or domain‑specific modelling) and apply it to complex business problems.
• Present clear, compelling, and well‑structured analyses to technical and non‑technical audiences, with a sharp focus on commercial implications.
• Translate ambiguous business questions into structured analytical problems; define success metrics and validation plans.
• Ensure models and outputs meet governance, documentation, and regulatory standards (e.g., GDPR, EU AI Act); promote robust workflows, version control, testing, peer review, and model risk governance.
• Contribute to evolving data science methodologies, internal tooling and governance frameworks.
• Translate model outputs into practical pricing recommendations, supporting underwriting strategy, rate changes, and portfolio management decisions.

• Data science experience in commercial insurance, with hands‑on experience developing or supporting pricing models (e.g., frequency/severity modelling, GLMs, or GBMs).
• Experience delivering advanced analytics or ML solutions that achieve sustained business impact.
• Experience leading analytical work streams or projects and coordinating inputs across multiple stakeholders.
• Advanced Python skills (pandas, Num Py, scikit‑learn; visualisation libraries).
• Proficiency working in cloud‑based Linux environments (e.g., Azure, AWS, GCP, Databricks).
• Understanding of software engineering best practices, including git, modular code design, and reproducible workflows.
• Excellent communication, storytelling, and stakeholder‑management skills; comfortable presenting to senior, technical, and non‑technical audiences.
• Experience mentoring or coaching junior colleagues to raise the bar for the team.

• You’re a hands‑on data scientist who enjoys solving real problems with data and communicates your thinking with clarity and confidence.
• You’re collaborative, open, and comfortable operating in fast‑paced, cross‑functional environments.

• 30 days holiday a year with the option to buy up to 2 additional days.
• Flexible working – opportunities include part‑time, job share, and compressed hours.
• Pension – automatically enrolled with employer contributions of…