This role will support and enhance the growing Hub, providing deep technical understanding of data science tools, techniques and technologies, and guiding junior data scientists through data science projects.
Dimensions This role requires a candidate with at least three years' data science experience, ideally within insurance or financial services. The candidate will have operationalised data science projects realising tangible commercial value. As well as the hard skills required (see competencies section below) it is of the utmost importance that the candidate can bring their personality to the team, mentoring junior members, managing long term data science projects with stakeholders at all levels and showing real passion and innovation in how we use data.
Key dimensions to this role are:
1. Machine learning and predictive analytics - Real world application of machine learning algorithms in a B2B setting, including regression, random forest, naïve Bayes, K-nearest neighbour, XGBoost and neural networks. Experience in Tensorflow is ideal.
2. Geospatial analytics - The candidate will have used a variety of mapping software (for example QGIS, ESRI, Mapbox) and will have experience in developing near time mapping applications with multiple data layers and formats (shapefiles, geojson, polygon and point analysis).
3. Natural language processing - Experience using NLP techniques, in particular text classification, entity tagging, network maps, sentiment analysis and semantic analysis with large volumes of text data.
4. Data engineering and ingestion - The candidate will be comfortable engineering data in Python/R and tools such as Dataiku & Alteryx. As the A&DS team is reliant on external as well as internal data, the role will involve a familiarity with sourcing and collecting data from the web, via web scraping and web crawling.
5. Project and stakeholder management - The candidate will have managed data science projects from scoping to delivery, ensuring other data team members (engineers, analysts and junior data scientists) are aligned and able to deliver. They will also be familiar with code repositories (TFS/Git) and principles of code management.
- Data Scientist
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