Great place to work - Recensione dipendente - Engineer presso Datatonic

+ Some brilliant people dotted around + Working with latest GCP tech + Engineering folk seem to fare better, on average + A lot of responsibility in your early career (can also be a con) + Shout out to the HR team and one particularly excellent Sales person (Sky account) who try their best to help the ML team out where possible + Working here gives great perspective on what to avoid in the future! + Most people who leave seem to go on to great companies with much better pay (+30-50% on average, I'd say) or into exciting non-profits

If you have another offer, I urge you to consider it over joining this company as a Data Scientist / ML Engineer. I know multiple recent joiners who quickly regretted joining and wished they had gone elsewhere. The reason I am writing this review is so that you can benefit from their (and my own) experiences. The details: - ML team turnover seems very high, resulting in almost no maintained knowledge or best practice. Median tenure within the remaining ML team seems to be around 3-8 months. I can think of only two people left who have been there over a year - Whole ML team now feels like a group of contractors rather than a team, as a result of turnover - ML team management do not seem to care about people and have no experience building ML systems in practice. Their focus is also split across two teams - DS/ML and Strategy/Engagement. This seems to result in poor oversight of project planning and execution - Maintaining client happiness seems to be repeatedly prioritised over work life balance, team happiness, or retention. Not saying that is necessary a bad thing for your bottom line, but don't act surprised when your retention continues to be poor - There seems to be no equity or partnership option, meaning there is almost no motivation for senior staff to stay on longer than 1-2 years - Some clients have over inflated expectations for ML performance (when considered against how much they are willing to pay for it). This, combined with stakeholder management as being the core focus of delivery teams, means technical staff seem to be asked to deliver sub-standard/rushed technical work on a regular basis - ML project delivery quality seems to have degraded since most of the original ML staff and management have left - Internal initiatives and employee group recommendations seem to be rarely taken on board (within the ML team). Similarly, improving internal processes seems to always take a back seat as soon as workload increases - Employee performance calibration between managers seems to be non existent, despite employee resource group recommendations - Not sure anyone knows what the CEO does

Datatonic is one of the most technically capable organisations I’ve worked with. The company operates at the forefront of AI, machine learning, cloud engineering and modern data platforms, which creates an environment where you’re constantly learning and exposed to new ideas. The quality of the people is exceptional. Colleagues are knowledgeable, approachable and genuinely invested in helping one another succeed. There is a strong culture of collaboration, mentoring and knowledge sharing that makes it easy to integrate into teams and feel supported. Learning and development opportunities are plentiful, whether through client engagements, internal knowledge-sharing sessions, formal training, certifications or hands-on exposure to cutting-edge technologies. The close partnership with Google also provides excellent access to expertise within the Google Cloud ecosystem. If you’re curious, ambitious and enjoy solving complex problems, you’ll gain more experience in a few months than many organisations provide in years.

Datatonic is a consultancy, and with that comes the realities of consultancy life. Client needs will always come first, which can mean context switching between engagements, balancing multiple priorities and regularly adapting to new environments and challenges. The pace is fast, expectations are high and you’ll often be operating at full capacity. While work-life balance is respected, there is an implicit expectation that consultants will go above and beyond when clients need support or opportunities arise to create additional value; this is not your standard 9-5. This environment won’t suit everyone. If you prefer highly predictable workloads, long-term ownership of a single product or a slower pace of change, you may find consultancy life demanding. However, for those who thrive on variety, autonomy and continuous learning, it’s an incredibly rewarding place to work; your career will accelerate faster than most.