Responsibilities
1. Apply the data science product lifecycle principles to new projects (Design, exploratory data analysis, building, evaluation, deployment, monitoring and maintenance)
2. Contribute to developing production data science models, monitoring their performance, and managing their lifecycle (retraining, optimising and upgrading)
3. Work on the end to end data solution including understandingplex 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
4. 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.
5. Write high quality python code using industry best practice for model training and deployment
6. Continuous development of knowledge base and experience, including researching new techniques and technologies,municating this back with the team
Our must haves
7. Experience of data science, advanced analytics or a genuine interest to learn.
8. Ability to conduct high quality research in a suitably timely manner working in both independently and in small teams as required by the task.
9. Familiarity with version control and other IT delivery tools is required
10. Understanding / identifying opportunity to apply machine learning knowledge to solve business problems
11. 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
12. Exceptional writtenmunications skills and effective presentation skills
13. Willingness to learn best practice in software development
14. Strong python programming skills
15. Experience of TDD (pytest or other testing framework)
Our nice to haves
16. Graduate or Postgraduate qualification or equivalent experience in a relevant discipline engineering, mathematics, physics, statistics
17. Experience of data science in finance, insurance or merce is an advantage but not required
18. Experience of deployment in a cloud environment
19. Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas
20. Experience with API development
21. SQL experience
22. Software engineering experience
23. DevOps / MLOps experience
24. Good working understanding of CI/CD
Diversity and flexible working at Hiscox
At Hiscox we care about our people. We hire the best people for the job and we'remitted 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.
#LI-EB1 #LI-HYBRID
Work with amazing people and be part of a unique culture Job ID R0017400