Salary | £55K – £65K
We are working with a leading eCommerce organisation that is looking for a Senior Data Scientist to join their fast-paced, agile, product engineering division. Working alongside a team of data specialists (Scientists, Architects, Engineers) you’ll play a key role in evangelizing data across their business.
This would suit a passionate Data Scientist/Statistician who has 3+ years experience in a similar role – eCommerce experience would be advantageous – using a variety of statistical and machine learning methods to help drive commercial decision making.
You’ll have strong communication, presentation and stakeholder management skills with exceptional insight into how data science can be used to provide large benefits in a large, customer focussed business – including reducing costs, optimising processes and improving customer experience by modelling customer behaviour.
As our successful Data Science Specialist, you’ll enjoy a fast-paced, continuous delivery environment, both working in cross-functional engineering teams as well with the wider Data community. Our client hosts many tech and data events, and this is something you enjoy getting involved in – speaking opportunities are available!
From a technical perspective, you’ll have a programming background with strong skills in SQL & Python development, good knowledge of public cloud platforms such as AWS or GCP and commercial experience using various machine learning techniques such as Regression, Gradient Boosting, Neural Networks, Random Forest or similar.
A Master’s degree in Mathematics, Statistics, Scientific subject or similar is expected although candidates with relevant Data Science experience outweighing academia will be considered, including in areas such as time-series modelling, applied statistics, mathematics or quantitative engineering.
Skills: Statistician, Statistical, Data Scientist, Mathematics, Analysis, R, SAS, Matlab, Statistical Programming, Regression, Machine Learning, MS SQL Server, Python, T-tests, ANOVA, Linear Models, Mathematical Modelling, Data Science, Time-Series, eCommerce, Engineering, Product, Agile.