Candidates’ skills/attributes should include:
- Strong numerical and mathematical background, ideally in statistics.
- Experience of statistical modelling (PhD level is not critical).
- Knowledge of and passion for different analysis techniques such as; regression, clustering and cohort.
- Data wrangling skills (R/Python – R will be assessed)
- Database skills (SQLite, MongoDB – SQL will be assessed)
- At least A grade A level maths, and BSc in maths/science/engineering >= 2.1 from a Russell Group university
- Minimum of 3 years of relevant work experience within data science and analytics
- Initial tasks will be maintaining a current view of data and building out datasets, and building predictive modelling
- Ideally evidence of interest in data science above and beyond the call of duty, ie Kaggle wins
Other desirable skills and experience:
- Good experience with R and Python
- Experience working with relational databases, especially SQLite and MongoDB
- Experience with RStudio or similar statistical analysis package.
- Good experience with integration technology for deploying R analytics inside web dashboards
- Understanding of the marketing industry
- Good understanding of build customer behaviour propensity models using a wide range of data sets (propensity-to-buy/propensity-to-churn).
The role will include tasks such as:
Building datasets from a wide range of different sources, with different structures to create a single unified database environment.
Building and developing multi-tiered matching scripts to match data sources into a master dataset.
Building statistical models and apply machine learning techniques to extract patterns from data sets, ability to build audience segments using regression and clustering techniques to build customer propensity and look-a-like models for more targeted marketing strategies.
Experience applying statistical techniques and machine learning algorithms to extract insights from real data
You should be a driven and motivated self-starter capable of working as part of a small team but equally capable of exploring data and analytical methods independently. The role will require a flexible approach to working hours. Candidates should be able to demonstrate previous data analysis work that they have carried out.It is vital that you are comfortable with working in an agile and lean technology start-up business environment. This will require a need to adapt to the unique challenges of working in a small business that is rapidly growing, and where the strategy, systems and processes are rapidly changing and evolving.
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