- £40-65K
- Full Time
- London North
- This position has been filled.
The Company
A digital marketing company who own a global online sports betting brand. This company supports on all services associated with the brand, including marketing analytics, compliance and legal, branding.
This is an exciting time to join the organisation as they have gone through a period of sustained growth over the past three years, doubling staff numbers and quadrupling online spend, resulting in brand awareness sky rocketing both domestically and internationally.
A non-corporate company culture with a casual dress code of trainers and jeans. The office is full of fun employee benefits including their own barrista, foosball and ping pong tables and break out working areas. This company also offers social benefits including trips to sports events and celebrity visits.
The Role
The purpose of this Data Scientist role is to focus on the most complex problems facing the sports betting industry and create data products that can be developed for their customers.
Your role will span key business areas including acquisition, retention and product. Primary responsibilities will involve model development using Big Data and statistical methodology, applying analytics techniques to understand customer behavioural change and full project life cycle management from design to presentation.
You would also work with the Data Engineering team to effectively deploy models into production at scale.
With a new focus on machine learning and predictive analytics, this company is creating a brand new Data Science team to help make accurate estimations about sports betting and player behaviours to optimise ROI. If you are about data and innovation, and excited by the idea of using cutting edge technology to work with big data then this Data team could be the place for you.
The successful candidate is likely to have:
– Demonstrable experience of applying techniques such as machine learning, generalised linear modelling, logistic regression, time series analysis, Bayesian methods, neural networks and complex data manipulation processing skills in order to build models.
– Experience of completing multiple end-to-end machine learning projects, from data wrangling through to implementation and testing.
– Experience using programming languages such as R, Python or similar to analyse, transform and visualise big data, as well as to implement machine learning algorithms.
– Experience with Big Data Technologies such as Microsoft Azure.
– Demonstrable problem solving skills.
Job Owner: d.prosser
