Applied Data Scientist

Applied Data Scientist

Department: Data

Employment Type: Permanent - Full Time

Location: London, UK

In Convex, we are shifting our focus from how we collect data to how we apply it. As a talented Applied Data Scientist, you will move beyond standard analysis to build intelligent solutions that directly empower our underwriting community and beyond to make cleaner underwriting decisions. This is a hands‑on, highly technical role that requires a "go-getter" mentality; someone who can identify a business problem, model the solution, and explain the "why" to non-technical stakeholders.

Convex is a data-driven insurance company adopting a culture of small, highly skilled teams building the core intellectual property while all operational needs are met with Software as a Service (SaaS) or outsourced providers. Our 3 strategic pillars are to be our customer’s favourite insurer, to achieve operational excellence and to make better decisions using data and technology. Central to this is the industry-leading usage of Generative AI, LLMs, and advanced data modelling.

We are looking for a tenacious, STEM-educated professional to join our team.

Ensuring we deliver value from data to our business stakeholders, by:

• Taking validated hypotheses that solve real world problems, turning these into production grade solutions.
• Moving beyond reporting to build predictive models and tools that help Underwriters make better, faster decisions.
• Working as a key member of a cross-functional squad, collaborating with engineers and business stakeholders to deliver end-to-end data products.
• Identifying opportunities to transition from simple data collection to advanced data usage that supports the Underwriting community's objectives.
• Acting as a technical leader by training team members on best practices in Python, modelling, and technical execution.
• Working with stakeholders to define, document, prioritise business requirements.
• Ensure business value of the requirements are understood by the squad.
• Communicating with stakeholders on timelines, expected outcomes and providing transparency.

Technical proficiencies and abilities:

• Deep proficiency in the Python Data Science ecosystem (e.g.,Pandas, Scikit-learn, PyTorch/Tensor Flow).
• Mastery of SQL is essential; experience with Snowflake is highly preferred.
• Solid experience with AWS in deploying solutions, including Generative AI services (Bedrock / Agent Core etc).
• Practical knowledge of Generative AI, including Large Language Models (LLMs) and agentic workflows.
• Strong understanding of Data Modelling and how to structure data effectively for scalable science projects.
• Must be able to work in a scaled agile environment involving cross functional execution teams.
• Source repository control and devops methodologies eg: github actions workflows.

Soft Skills:

• Ability to simplify and translate complex data findings to cater to various stakeholders
• A desire to train and upskill others within the team.
• A proactive mindset with the ability to work autonomously and propose new ideas to the business.
• Must be able to communicate with stakeholders effectively and keep them updated on scope, timelines, and outcomes.

Preferred experience:

• Direct experience working within the General Insurance or Specialty Insurance markets.
• A deep understanding of the Underwriting lifecycle, including risk selection, pricing adequacy, and exposure management.
• Strong STEM background with a highly numerate degree
• Candidates with an Actuarial background (either qualified or making significant progress through exams) are highly encouraged to apply.
• The ability to bridge the gap between traditional actuarial science and modern machine learning is a significant advantage.
• Proven track record of building models that have been deployed into a live production environment (not just "sandbox" projects).
• Experience handling messy, disparate insurance datasets and transforming them into structured, high-value inputs for predictive modelling.

• Competitive Salary
• 30 days Annual Leave
• Birthday Leave
• 10% Employer Pension Contribution
• Private Health Insurance Medical Cover
• Group Income Protection
• Life Assurance Cover
• Enhanced Parental Leave
• Annual Health Check
• 3 days of Volunteer Leave each year
• 10 days of help with care (elder/ childcare) through Bright Horizons
• £1,300 to spend on learning & wellbeing
• Give as You Earn
• Cycle to Work
• Season Ticket Loan