WE ARE HIRING! We’re looking for problem solvers with a passion for data. Be part of a dynamic data technology consultancy: https://thinkingmachin.es/careers/
Thinking Machines is a technology consultancy operating at the intersection of AI, business, and data design. At Thinking Machines, we make our clients successful by building AI & data platforms to solve high impact problems - from identifying where to make the next billion dollar capex investment by applying AI on satellite images, to delivering poverty and hazard maps for civic organizations.
We’re a company made up of intellectually curious, civic-minded, forever-learning individuals, and we believe that great data science products are built with care for people. Our team has a mixed background ranging from Stanford Computer Scientists and Engineering Graduates, UX/UI Designers, Software Developers, and Management Consultants.
Rating Reviews
Rating is calculated based on
1
review and is evolving.
Pros: Working as a Data Scientist here has been a positive journey. The team is super supportive, fostering great learning opportunities in AI and analytics. The company culture is collaborative, and the work flexibility is a big plus for work-life balance. It's an ideal spot for career growth in the tech industry.
Cons: Sometimes, project deadlines create intense workloads. Better communication on company-wide strategy would be helpful.
Advice to Management: Continue to prioritize work flexibility and the supportive culture. Consider refining communication for company-wide strategic updates to ensure everyone feels fully aligned.
Show more
Common Questions About Thinking Machines Data Science
What is the day-to-day working culture like for a Data Scientist at Thinking Machines, especially in their Singapore office?
The culture at Thinking Machines emphasizes collaboration and continuous learning, which is beneficial for Data Scientists. You'll find a supportive environment where team members actively share insights and work together on challenging projects, fostering professional growth within the data science field.