Discover
Companies
Browse top employers
University Rankings
Malaysia's best unis
Salary Insights
Know your market worth
Career Tools
All Tools
Browse every career tool
Job Swipe
Tinder-style job matching
CV Checker
AI-powered CV review
Career Planner
Map your career path
LinkedIn Optimizer
Sharpen your profile
LinkedIn Roaster
Brutally honest review
Career Wrapped
Your year in review
Professional Persona
Discover your work style
Financial Services
Snapshot
1000 total reviews
Source
Glassdoor
100% of reviews mention positives
Page
5 / 100
Director of infrastructure
Robust Value for şnternaland external customer
Employee benefits Comnınication Imperative Work and life balance
Senior training manager
very good social climate with my teams
extended working hours when launching new products
Senior consultant
Work from home and nice building
Management sucks and will spit you out as soon as you make one mistake. Chief officers know nothing, not trained. Changes for sake of changes. Too political and looking after themselves rather then the staff and clients
Senior project leader
The greatest strength of Zurich is its ability to attract intelligent, thoughtful and passionate people.
The size of the organisation and relatively conservative outlook means that innovation and taking risks are uncommon. However, this differs significantly by department.
Dlp analyst
True flexibility (hibryd and fully remote positions available, and results oriented mindset rather than strict-hours-focused). The company's culture regarding employees upskilling and professional grow are remarkable.
The salary in this particular position is rather low.
Anonymous employee
The work was quite easy, and there was little pressure to deliver.
The data science team has a chronic lack of experience, and is lead by people without technical expertise. The result is that projects are haphazardly slapped together without any real thought given to use-case, meaning projects drag on for years and often lead to marginal or no impact on the business. Even worse, the lack of technical expertise means that no thought is given to appropriate solution architecture (e.g. projects are "productionised" through shared folders and Excel documents, low-code RPA processes are used instead of actual software), so the often pointless projects also come saddled with a mountain of technical debt, with little appetite from management to fix it, or invest in the people and skills needed to do things properly choosing instead to endlessly rotate graduates and apprentices through the team). There was no code review process, the team had not adopted minimum engineering standards such as appropriate testing or correct use of version control. Appropriate tools are not used for development, because management dictate the solution design, despite lacking appropriate experience. ML engineers are expected to be code monkeys implementing management's poorly-conceived ideas; it is not a good place to learn new skills or develop meaningful experience as an engineer, because there are no experienced people to learn from or work with, and the projects rarely add meaningful value.
New business consultant
* flexible work arrangements * competitive salary
- - - - -
Underwriter
Great culture within various teams
Not any come to mind
Big data engineer
Compensation time when you exceed your hours
As many big companies. Change is slow
Direct sales
commission on sales Monday to Friday
terrible salary. horrendous higher management driven by their own success