Junior Pricing Data Scientist

Description

The company started in 2017 and has grown from 3 to 700+ people.

It has reached unicorn status, raised about £140M over three funding rounds, and become profitable.

It insures millions of drivers and has lent millions in car loans.

Within the next 10 years it aims to become one of the largest financial services providers in the world, growing through existing products and new ones.

It wants people who are ambitious, commercially minded and never settle for good enough. Autonomy, ownership, improving rather than coasting, raising standards and collective success over self-interest are valued.

The pricing team applies quantitative methods to real insurance problems. You will see how pricing decisions work in practice and turn data into results, working alongside a senior pricing team member. The goal is to build the judgement and independence to eventually lead increasingly substantial work.

Responsibilities

• Take on scoped analytical and data-driven projects with pricing colleagues, with more responsibility as your experience grows.
• Apply mathematical, statistical and machine learning methods to practical pricing questions, linking your analysis to the decision it needs to support.
• Present findings clearly, keep colleagues in other areas updated on progress, and follow up on agreed actions.
• Act on feedback to strengthen your work, your data science methods and coding practice, and your grasp of the commercial side of insurance pricing.

Requirements

• A strong academic record and a research master's or PhD in a quantitative field such as mathematics, physics or econometrics.
• Experience applying quantitative methods or machine learning to a practical problem through study, research, a personal project or work.
• The ability to explain how your approach fits the problem, not just the theory behind it.
• A willingness to learn, seek feedback and build towards working independently.
• Clear communication of your reasoning and findings, and keeping colleagues informed.
• Follow-through on agreed actions and ownership of your work.
• Preferred: industry experience, such as a placement, internship or work while studying, or between research master's or PhD study.

Conditions

London, hybrid, with 3 days in the office.

Visa sponsorship is not available for this position.

Hiring process: an initial 30-minute call with the Talent Team, a combined past experience and technical interview of 90 minutes, and onsite culture interviews of 90 minutes.

Benefits

• A bonus scheme designed to reward high performance.
• Private medical insurance through Vitality and mental health support through Oliva.
• A personal learning budget and 2 dedicated L&D days a year.
• A monthly flexible benefits budget that you allocate however you prefer.
• 25 days of holiday plus bank holidays.
• 4 weeks per year of Work From Anywhere.