Product Management is arguably the most coveted generalist tech role. Some describe product managers (PMs) as “Mini CEOs“ of their product. Others use elaborate ven diagrams placing product management at the intersection of engineering, business and design, wearing all 3 hats and weighing all tradeoffs. Thus, it is no surprise that many perceive product managers as jacks of all trades. That said, if we look closely at the state of PMs, especially at mature product organizations, we see a different story.
While its true PMs interact with various stakeholders and drink from the fire hose on a daily basis, many…
“Product Operations” is a nascent but fast-growing field. What is it, and what skills does it require?
I first heard of Product Operations (POps) when I joined Uber in 2019. The product operations function was kicked off at Uber back in 2015 by Blake Samic. As the Uber machine scaled globally, a middle layer between Product and operations teams around the world was needed to prioritize and tackle the most impactful tech and business problems.
With scale comes complexity. Silos slowly creep up, and mission-critical tasks start to fall between the cracks. Enter Business Operations (BizOps) — a cross-functional role with the sole mandate of getting stuff done and keeping the company on track.
“What is modern housing? Modern housing is a collective effort to create habitable domestic environments within the framework of integrated communities. Such housing demands not merely an improvement of the physical structures and the communal patterns: it demands such social and economic changes as will make it available to every income group.” — Lewis Mumford
“When technology makes density more valuable, cities will be more attractive. When technology makes density less valuable, cities will be less attractive.” — Rohit T. Aggarwala from The First Principles of Urbanism: Part I
Following the 2008 financial crisis, the world witnessed the incredible growth of start-ups in mobility, food delivery, co-living and co-working. Indeed, I am talking about the likes of Uber, DoorDash, Airbnb and WeWork whom by many estimates have a combined valuation exceeding $100B, and a footprint that exceeds many of their traditional counterparts in their respective fields.
“You can’t plan a career decades ahead. Some of the jobs and places that will interest you then don’t exist now — and some that interest you now will be gone then.” — Adam Grant
Goal setting theory by Locke¹ is based on the fact that conscious human behavior is purposeful. Goals can be classified into two categories: short-term and long-term.
Traditionally, short-term goals are defined as the ones that could feasibly be completed in 3–12 months, while it usually takes more than one-year to achieve a long-term one.
Fortunately, short-term planning…
The future of banking starts here
What does Google, Apple, Facebook, Amazon and Uber all have in common? They are all in pursuit of the global payment industry.
Google launched its digital wallet as early as 2011 and followed with Google Pay in 2017. Apple recently partnered with Goldman Sachs to offer credit cards, and Apple Pay has been available for consumers since 2016. Amazon has a suite of financial products and other companies such as Uber and Facebook are following suit.
BigTech’s push into fintech can be regarded as good news for us consumers — the main beneficiaries of…
A couple of months ago, I left my job as a Data Scientist at Nulogy — A Toronto based SaaS company. During my last 6 months, the Data Science team was transitioning from the POC phase to actually building the company’s first machine learning product. As with any product team, we needed a person to help manage what is left of our data-product life cycle. That is, we needed a Data Science Product Manager (DS PM). And, because of different changes in the organization at the time, I got to temporarily wear that hat. …
You have just been hired as a Data Scientist at a small software company. You are feeling ecstatic! Your hard work and perseverance has finally paid off. It is time to put your statistics and machine learning knowledge into action. You have finally joined the data revolution. Congrats!
Day 1 arrives, and everyone is excited to meet this “Data Scientist”. The company has never hired a data scientist before, so expectations were unrealistically high. But, you are not worried. Your supervisor, who probably is not a data scientist herself, asks how she can assist you on your first day. “Just…
UrbanTech enthusiast, ex-Data Scientist and current Strategy & Operations Manager at Uber