IYKRA

Pros: IYKRA offers decent remote work options, which is a lifesaver as a Data Analyst Instructor. I've got pretty flexible hours for most of my data science training tasks. It's a big plus for work-life balance.
Cons: Sometimes the AI consulting project deadlines mean less flexibility than you'd hope for. You can't always dictate your schedule, even with a remote setup. It gets tough during crunch times in this startup environment.
Advice to Management: Keep pushing for true asynchronous work whenever possible. Help teams manage client expectations better so flexible hours aren't always compromised.

Pros: I like that IYKRA offers some hybrid work flexibility. For Junior Data Consultant roles, I usually get my work done within standard hours. It's not a crazy startup grind all the time at the Jakarta office.
Cons: Sometimes project deadlines mean working longer. It can be hard to say no to extra tasks, especially in this growing data consulting startup. Some managers could be better about protecting personal time.
Advice to Management: Try to enforce boundaries around project deadlines. It would really help staff, especially those in entry-level data roles, manage their time better and prevent burnout.

Pros: The base salary for a Junior Data Scientist in the Jakarta office was pretty solid when I joined, especially for a local tech startup. They do offer some chances for training in data analytics tools, which is helpful.
Cons: Raises aren't very common, even if you're performing well. The health benefits package isn't great; you're basically on your own for dental or optical care. I also wish there was more transparency about compensation bands for data roles.
Advice to Management: Please review the salary bands for data science roles more regularly and definitely improve the benefits package, especially health coverage. More transparency on pay would really help morale.

Pros: The remote work flexibility is a big plus; I could work from my home in Jakarta easily. You generally get decent time off, and it's not a super strict 9-5, which helps with personal stuff.
Cons: As a Data Analyst, the workload for data analytics projects can sometimes be pretty heavy. Deadlines often mean working extra hours, especially at month-end. It's not always easy to log off on time.
Advice to Management: Try to better manage project scopes and set more realistic expectations for deadlines. Help us protect our personal time better.