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Job Type: Permanent
Build a brilliant future with Hiscox
The technology team for Hiscox UK is an integral part of the business and is central to the Hiscox strategy, driving the technology agenda that underpins the UK Retail business strategy. We are a team who push the organization to think differently and we are solutions and outcomes focused. We are therefore looking to attract / recruit people who aren’t afraid to challenge how things are done and approach their work with a pioneering mindset. We want problem solvers who seek to collaborate and understand the business challenges, and can deliver technology solutions. We are trusted for our track record of delivery and respected for our commercial thinking and have earned our place at the table.
The role
As a Data Scientist at Hiscox you will have the opportunity to apply your skills to a wide range of business problems as part of a core team of data scientists, engineers and analysts. We operate in small teams adopting a version of Agile that keeps us on a 2 week review cycle. Our objective is to deliver business value using an MVP approach that will then scale to a fully developed and realised solution.
You will have the opportunity to work with a range of stakeholders to determine new opportunities in decisioning (new business and policy management), intent, pricing and monitoring. We will be operating across a number of business functions, solving a wide variety of problems which will involve changing context fairly often.
We are looking for people that are both hands-on Data Scientists and also good communicators that enjoy working in a team environment. We will both deliver data science solutions, but also help the business understand the opportunity data science brings. This is an ideal role for an individual who is passionate about the use of Data Science to influence decisions and is keen to learn more about delivering value through the use of data.
You will be expected to conceptualize new ways of doing things, communicate vision simply and effectively to key stakeholders, and see these visions through to implementation.
Key Responsibilities
- Apply the data science product lifecycle principles to new projects (Design, exploratory data analysis, building, evaluation, deployment, monitoring and maintenance)
- Contribute to developing production data science models, monitoring their performance, and managing their lifecycle (retraining, optimising and upgrading)
- Work on the end to end data solution including understanding complex business challenges, designing scientific solutions, working large and small data sets (including 3rd party and internal data of a wide variety), using cutting-edge machine learning or statistical modelling techniques to derive insights
- Work collaboratively with data scientists, data engineers and other technical people including pricing teams in order to help support maturation of analytics practice within the organization.
- Write high quality python code using industry best practice for model training and deployment
- Continuous development of knowledge base and experience, including researching new techniques and technologies, communicating this back with the team
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Our must haves
- Experience of data science, advanced analytics or a genuine interest to learn.
- Ability to conduct high quality research in a suitably timely manner working in both independently and in small teams as required by the task.
- Familiarity with version control and other IT delivery tools is required
- Understanding / identifying opportunity to apply machine learning knowledge to solve business problems
- Experience in developing predictive and prescriptive analysis (predictive modelling, machine learning or data mining) used to draw key business insights and clearly articulate findings for target audience
- Exceptional written communications skills and effective presentation skills
- Willingness to learn best practice in software development
- Strong python programming skills
- Experience of TDD (pytest or other testing framework)
Our nice to haves
- Graduate or Postgraduate qualification or equivalent experience in a relevant discipline e.g. engineering, mathematics, physics, statistics
- Experience of data science in finance, insurance or Ecommerce is an advantage but not required
- Experience of deployment in a cloud environment
- Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas
- Experience with API development
- SQL experience
- Software engineering experience
- DevOps / MLOps experience
- Good working understanding of CI/CD
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Diversity and flexible working at Hiscox
At Hiscox we care about our people. We hire the best people for the job and we’re committed to diversity and creating a truly inclusive culture, which we believe drives success. We also understand that working life doesn’t always have to be ‘nine to five’ and we support flexible working wherever we can.
No promises, but please chat to our resourcing team about the flexibility we could offer for this role. We’ve introduced new hybrid ways of working to encourage a healthy work life balance. We anticipate the successful candidate for this role will be in the office up to 2 days per week. We see it as the best of both worlds: structure and sociability on one hand, and independence and flexibility on the other.
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Work with amazing people and be part of a unique culture
If you want to help build a brilliant future; work with amazing people; be part of a unique company culture; and, of course, enjoy great employee benefits that take care of your mental and physical wellbeing, come and join us.
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We’re a global, specialist insurer headquartered in Bermuda and listed on the London Stock Exchange. With 3,000 employees and 32 offices in 12 countries we’re a business with lots of opportunity for people with talent, spark and lots of ambition.
If you want to build a great career with a company that prioritises strong values – such as integrity and courage – where our people always pull together to do the right thing for each other and our customers, then we’d love to hear from you.
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