Senior Pricing Data Scientist
Role details
Job location
Tech stack
Job description
Your main responsibility will be to continuously improve and innovate conversion and Life-Time Value (LTV) models used within the retail pricing team. The overall aim is to set the optimal commissions/prices that maximise sold LTV for every individual customer and reduce money left on the table.
Your models will be the source of truth when it comes to understanding our position in the market and will be used to select the level of profitability vs sales share we aim for each price deployment.
You will work with a completely customisable pricing system (built, managed and maintained in house, in Python) meaning data, pricing rules, models and logic can all be changed and tested by the retail pricing team with no Developer involvement. As such you are encouraged to try out new innovative ideas that other companies are not able to implement due to their rigid systems.
As well as being responsible for conversion rate and elasticity models, you will also be responsible for the maintenance and improvement of our market premium models - the most influential feature within our conversion rate models. As we have a number of external market premium data sets, you will be tasked with identifying the best structure of how to use these data sets/model(s) within our modelling ecosystem.
This role will:
- Be instrumental to the growth of the business using data to develop and optimise a variety of strategies in the retail pricing space.
- Collaborate closely with the Retail and Technical pricing teams to determine better positions in the market.
- Be very technical with most of your time spent improving and innovating using Python.
Requirements
We would love to hear from people with the following skills and experience for this role:
- 4+ years experience working in personal lines home insurance pricing.
- A specialism in conversion rate modelling and market modelling is desired.
- Knowledge of market dynamics and elasticity is essential.
- High quality numerate degree (Mathematics, Data Science, Physics, Engineering etc.). Degrees from other disciplines will be considered with relevant industry experience.
- An understanding of statistics and machine learning best practices.
- Competent using Python and its data science ecosystem for data manipulation, data visualization and statistical modelling.
- Excellent data manipulation and reporting skills using SQL and MS Excel.
- Strong problem-solving skills: able to effectively analyse new situations, and to suggest and implement pragmatic solutions.
Benefits & conditions
We think we have a fantastic company culture and welcome new team members with open arms. We also offer a great range of benefits, including:
- A genuinely flexible approach to work. We are really supportive of you flexing your hours and location to help you keep everything in your life in balance.
- Opportunities to focus on your professional growth whether that's through training or other personal development opportunities - we want you to build your long-term career with us.
- Home insurance with Homeprotect at 50% discount for all employees and 15% for friends and family.
- An in-house wellbeing programme including seminars and workshops from wellbeing coaches and professionals.
- Home working starter kit and money to spend on additional equipment you may need.
- Charitable giving scheme, so you can donate to our partner charity, or one of your choice.
- The opportunity to work alongside brilliant people, because this isn't something that every organisation can offer!
On top of that, we also offer all the standard stuff, like:
- 25 days' holiday (plus bank holidays) and the ability to buy and sell >5 days annually.
- Private Health Care with 24-hour, 7-day access to range of doctors and counsellors.
- Life insurance which provides cover to the value of four times your salary.
- Annual discretionary bonus scheme (up to 20%).
- Pension contribution.
- Free fruit and really good coffee for the days you come into the office and also occasional brunches to connect and bond with colleagues over food.
- Local and national retail discounts .