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Applied Data Scientist
Convex
- London, England, United Kingdom
- London, England, United Kingdom
Über
Data
Employment Type:
Permanent - Full Time
Location:
London, UK
Description 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.
Key Responsibilities 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.
Skills Knowledge and Expertise Technical proficiencies and abilities:
Deep proficiency in the Python Data Science ecosystem (e.g.,Pandas, Scikit-learn, PyTorch/TensorFlow).
Mastery of SQL is essential; experience with Snowflake is highly preferred.
Solid experience with AWS in deploying solutions, including Generative AI services (Bedrock / AgentCore 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.
Benefits
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
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Sprachkenntnisse
- English
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