Data Science Manager

AEGIS London; London; On-site; GBP 60,000 - 100,000; Full time

Job summary

An established industry player is seeking a skilled Data Science Manager to enhance their data-driven capabilities. This role involves ownership of innovative projects, from Algorithmic Risk Ranking to Machine Learning Profitability Analysis, aimed at improving risk selection and profitability. You'll collaborate closely with underwriting teams, data engineers, and technology experts to define strategic data requirements and deploy automated analytics solutions. The ideal candidate will possess strong programming skills, particularly in Python, and have a solid background in data science or actuarial roles. Join a forward-thinking company that values inclusivity and continuous improvement, and make a significant impact on their data strategy.

Qualifications

• Proven management experience and stakeholder management skills.
• Expertise in data science techniques and advanced programming skills.

Responsibilities

• Lead data science capability for underwriter decision-making.
• Collaborate with Data Analysts and Actuaries on insights.

Skills

Management Experience

Stakeholder Management

Data Science Techniques

Python Programming

Statistical Analysis

Collaboration with Data Engineers

Data Use Case Development

Education

Solid Academic Background

Tools

Azure Data Factory

SQL

Synapse Analytics

PowerBI

Job description

Time Type:

Full time

Working Pattern:

Purpose of the Role

Ownership, development, and enhancement of Data Science projects such as Algorithmic Risk Ranking, Digital-Follow, Machine Learning Profitability Analysis, and Pricing. Enhance the Data Science capability of the business to support underwriting teams with insights, improve risk selection and profitability, and aid automation and efficiencies across departments.

Alongside the Data Analytics Manager, define strategic data requirements for delivering data consumption use cases. Build Data Science use cases and integrate them into data assets, dashboards, and 'The Underwriter Workbench'. Interact with underwriters, data engineers, and technology teams to capture, prioritize, and document business and technical requirements, leading to deployment of automated, optimized analytics solutions.

This role requires strong data science and programming skills, along with statistical, data manipulation, and analysis capabilities. Effective communication and collaboration with Data Analytics and Actuarial teams are essential. Contributions to management and board reports and team management skills are also expected.

Duties and Accountabilities

1. Lead the data science capability to drive data-led algorithms for underwriter decision-making, e.g., Risk Ranking frameworks.
2. Partner with Digital Trading to analyze portfolio profitability, build digital rule sets within risk appetite constraints.
3. Refine pricing models with the actuarial team using advanced statistical techniques.
4. Use AI to automate and improve data pipelines and analysis, e.g., Cause of Loss Classification.
5. Collaborate with Data Analysts and Actuaries on external data analysis and insights.
6. Support and promote the team's capabilities with the Head of Data Analytics and Portfolio Underwriting.
7. Participate in 'Design Authority Group' to develop Data Science models and systems.
8. Work with actuaries on the Pricing Working Group to advance statistical methods and oversee model changes.
9. Manage a team of Data Scientists, organizing and prioritizing projects.
10. Define strategic data requirements with the Data Analytics Manager, facilitating stakeholder communication, documenting requirements, and ensuring effective data solutions.

Skills, Knowledge, and Experience

The ideal candidate will have:

• Proven management experience
• Stakeholder management skills, including engagement with technical and senior stakeholders
• Expertise in data science techniques
• Advanced programming skills, preferably in Python
• Strong statistical and data analysis skills
• Solid academic background
• Experience collaborating with Data Engineers, Architects, and Tech teams
• Significant experience in Data Science or Actuarial roles, ideally in Lloyd's
• Proficiency in IT packages and data technologies such as Azure Data Factory, SQL, Synapse Analytics, PowerBI (preferred)
• Good organizational and communication skills
• Experience supporting data use case development

AEGIS Values

We are committed to fairness, respect, openness, inclusivity, ambition, continuous improvement, and investing in our people's potential. We value diversity and encourage applications from all backgrounds. For accessibility support during the application process, contact us at [phone] or [e-mail]. We support flexible working practices to help you reach your full potential.