Data scientist Median annual salary: $112,590 Data scientists continue to be in high demand, with the Bureau of Labor Statistics (BLS) reporting that employment is expected to jump 34% by 2034. The job involves using special analytical tools and techniques to gather and interpret data for their employers. Since much of the work is done in the office, it can easily transition to remote work.
Companies are hiring armies of people with "product manager" on their business cards, but they're treating them like project management with better vocabulary. Frankly I see it a lot with enterprise clients. Teams are drowning in tactical decisions and they're optimizing for activity over outcomes. The result is not ideal: Products that ship on time but solve all the wrong problems. Roadmaps packed with features nobody asked for.
I've spent 15+ years building across multiple tech ventures and cultures - starting in Vietnam, sharpening my craft in Japan and Singapore, then expanding to the U.S., Australia and Europe. Each stop taught me how different ecosystems turn constraints into capability: how to ship products under pressure, build companies from zero, grow talent pipelines and lead teams through the hardest execution challenges.
Some product managers become bottlenecks because they want to control all decisions and information. For others, company culture creates bottlenecks. Regardless, whether it's excessive approvals, fear of failure, or unclear accountabilities, product managers often become the single decision maker for product development. It's a lot of pressure to have team members waiting on you for something and to unblock them in their progress.
Every CEO knows the feeling of promised features taking months longer than expected, simple changes breaking unrelated systems, and top engineers fighting fires more than they build the future. Welcome to technical debt: the detritus of yesterday's innovation that increasingly blocks progress today. The crucial reality is that tech debt isn't an "IT issue"-it's a business strategy problem that directly impacts your bottom line, competitive positioning, and organizational resilience.
Evidence maps are logical tools for consolidating data and insights, offering clarity in decision-making amidst a sea of qualitative and quantitative data gathered from multiple tests.
Create claims 30,000 monthly active users, that it processes more 20,000 projects daily, and that its Frontier AI agent is "so reliable you can build entire apps without looking at the code once, under the hood."
Nora emphasizes the importance of curiosity in identifying gaps or assumptions in product management, advocating for a culture of openness and diverse perspectives. She believes that understanding the audience is crucial, as this aligns closely with product strategy and helps to create meaningful interactions.
The rise of product operations didn't happen overnight. It started with changing expectations around what product managers should focus on, then the pandemic created three specific challenges that made dedicated operational support essential.
Every product leader used to brag about how quickly they could ship their product. However, with the rise of new regulations, today's top PMs brag about their ability to ship fast while also showing their work, dataset lineage, bias tests, and audit hooks before any code reaches production.
Transparency and clarity are fundamental to establishing trust in product management. Users want assurance that what they purchase will meet their needs and work as expected.
Documentation isn’t just a formality; it’s essential for understanding how software is assembled, ensuring we can reproduce any version of any product at any time.
The shift from traditional product management to more AI-driven development is indeed a cultural change, especially in high-stakes industries where risk aversion is natural.
Everybody wants to ship code every moment they can. I have friends who go to production twice a day, and small, iterative chunks are the right way to endure your business.
Technology must align with customer needs, serving as an enabler for business objectives. A product-led approach prevents the creation of solutions that may be technically impressive but commercially irrelevant.
The obsession with root-cause analysis remains constant as I focus on understanding what prevents one more successful trip, whether debugging a SQL query or redesigning a reservation flow.
One of the most common misconceptions is that healthcare platforms and products are difficult to build to benefit patients. Outsiders often think that because the healthcare ecosystem has competing incentives, none of them prioritize the patient experience.