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- Tasks: Build intelligent solutions to empower underwriting decisions using data and advanced modelling.
- Company: Join Convex, a data-driven insurance company with a focus on innovation.
- Benefits: Enjoy competitive salary, 30 days leave, private health insurance, and learning budget.
- Why this job: Make a real impact by transforming data into actionable insights for the underwriting community.
- Qualifications: Proficiency in Python, SQL, and experience with Generative AI and data modelling.
- Other info: Dynamic team environment with opportunities for professional growth and development.
The predicted salary is between 36000 - 60000 £ per year.
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.
- 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.
- 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.
- 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
Applied Data Scientist employer: Convex
Contact Detail:
Convex Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Convex. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving Python and predictive modelling. This will give you an edge when discussing your experience during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your SQL and Python skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Convex team!
We think you need these skills to ace Applied Data Scientist
Some tips for your application 🫡
Show Your Passion for Data: When writing your application, let us see your enthusiasm for data science! Share specific examples of how you've used data to solve real-world problems and how that aligns with our mission at Convex.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Applied Data Scientist role. Highlight your experience with Python, SQL, and any relevant projects that demonstrate your ability to build predictive models and tools.
Be Clear and Concise: We appreciate clarity! When explaining your experiences and skills, keep it straightforward. Use bullet points where possible and avoid jargon that might confuse non-technical stakeholders.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Convex
✨Know Your Data Science Tools
Make sure you brush up on your Python skills, especially with libraries like Pandas and Scikit-learn. Be ready to discuss how you've used these tools in past projects, particularly in building predictive models or deploying solutions in AWS.
✨Understand the Business Context
Convex is all about applying data to solve real-world problems. Familiarise yourself with the underwriting process and think of examples where your data solutions could directly impact decision-making. This will show that you can bridge the gap between technical and non-technical stakeholders.
✨Prepare for Technical Questions
Expect to dive deep into your technical expertise during the interview. Prepare to explain your experience with SQL, Generative AI, and data modelling. You might even be asked to solve a problem on the spot, so practice articulating your thought process clearly.
✨Show Your Collaborative Spirit
Since this role involves working in cross-functional teams, be ready to share examples of how you've successfully collaborated with engineers and business stakeholders. Highlight your ability to communicate complex findings in a simple way, as this is crucial for ensuring everyone is on the same page.
