Senior Data Scientist - up to £78k - 90% WFH (Manchester office) - Insurance Sector
There’s a myth that insurance isn’t an interesting sector to work in as a Data Scientist.
It’s not strictly true. Not here, anyway.
First of all, this company has many different types of customers.
This means you probably won’t have a single model or way of working that satisfies all parties simultaneously.
Creating valuable things for multiple customer types is an interesting challenge.
The culture is also very entrepreneurial; you won’t find yourself working on the same thing for over six months.
You can also choose whether you work from home or the office. You won’t be mandated to work a set amount of days in the office per week or month.
There’s also scope for you to become a Lead Data Scientist within a couple of years.
Other perks include access to a DataCamp subscription and the ability to attend networking events and conferences.
What you’ll be doing
Developing ambitious solutions.
Leveraging vast data assets and state-of-the-art processing capabilities.
You’ll be the technical lead in developing predictive models that solve business challenges through one-off analysis or bespoke modelling
This is a broad role, so you’ll have a hand in most things.
You’ll be building models and have the fundamental ownership of some models.
This will include:
- Risk classification
- Development of models for new products or specialised risks
- Testing of innovative predictive modelling techniques
- The development and maintenance of predictive models
- Being involved in the development and testing of state-of-the-art hyper-parameter tuning methods
- Driving efficiency in the tuning of standard machine learning processes
Who you’ll be doing it for
A leading provider of private insurance.
Founded in 2001, they now have over 7000 employees.
Who you’ll be doing it with
You’ll join an existing team of four other Data Scientists - a Lead, two Data Scientists and a grad.
You’ll report to a Data Science Manager.
The experience you need
- A degree or master's in statistics, data science or an equivalent field
- A minimum of 3 years experience in data science
- Experience and detailed technical knowledge of GLMs / Elastic Nets, GBMs, GAms, Random Forests, and clustering techniques
- Experience in programming languages (e.g. Python, Pyspark, R, SAS, SQL)
How to apply
Click "Apply" or book a call in Tom Smith's diary here.