Technical Lead, Data Scientist
MS Amlin is part of a global top-10 insurance group MS&AD, with three main legal entities operating in the Lloyd’s, UK, Continental European and Bermudian markets. We have an enviable reputation for our customer knowledge, claims service and the specialist insurance and reinsurance expertise we apply. We provide the type of security leading organisations need to break new ground, innovate and offer life-changing services and amenities to some of the world’s most challenging regions. Our record extends back over 300 years and today we have more than 1800 people in more than 20 locations worldwide.
We are experts in underwriting, with both technical capability and deep knowledge of the areas we insure. Our claims service aims for equality, with efficient, fair and timely claims management.
We’re going through an exciting period of modernisation and transformation for which we need entrepreneurial thinkers to help execute our strategic vision for growth. We’re on a dynamic path and we need you to help shape it.
MS Amlin is committed to taking a flexible approach to working, with a Work Life Better scheme to allow our employees more control over when and where they work, while still continuing to meet our client demands. This flexible approach continues into our benefit scheme, with a competitive package and attractive lifestyle fund.
ABOUT THE JOB
MS Amlin has a growing Analytics and Data Science (A&DS) team operating within a London Digital Hub whose role is to maximise the value the organisation gets from data. We are searching for a technical lead who will support and enhance the growing Hub, providing deep technical understanding of data science tools, techniques and technologies, and guide more junior members through data science projects.
This is where you come in.
You can help MS Amlin to achieve this with the following:
1. Build and deliver operational data science applications to teams across the business, with projects ranging from risk selection, pricing, triaging, fraud detection, telematics, and more.
2. Ensure the accuracy and predictive power of algorithmic solutions within these projects, managing the deployment and maintenance of machine learning solutions in claims, underwriting and elsewhere as required. Innovate new approaches and technologies to upskill the team, while assessing the methods used across the team to ensure work quality.
3. Scope and drive the pipeline of ideas and new projects coming into the Hub, in particular working closely with the data analysts and engineers to ensure consistent, governed and efficient use of data.
4. Manage and communicate technical results clearly to stakeholders, showing passion for using data to solve key business problems.
What we are looking for:
This role requires a candidate with at least five years of data science experience, ideally within insurance or related fields. The candidate will have operationalised analytics projects realising tangible commercial value.
Key technical capabilities to this role are:
1. Machine learning and predictive analytics – Real world application of machine learning algorithms in a business setting, including regression, random forest, naïve Bayes, K-nearest neighbour, XGBoost and neural networks.
2. Customer analytics – Experience with a variety of customer analytics, such as reducing churn, driving new business/upselling, improving engagement or customer experience, B2C pricing and elasticity, etc. ideally in an insurance or financial services environment.
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 preparing data in Python/R and tools such as Dataiku & Alteryx. As the 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 APIs.
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.