Over the past months I’ve been telling you about my take on risk management, automated decisions, digital goods and various other areas. I am now starting to look for candidates for my team to deal with these exact areas within Paypal – so if you’re one or think you know one, please let me know. Find the formal JD in the eBay site with req number 38550BR. But read on before that - the description in this post is much more important).
The team is Paypal's New Ventures Risk team, in charge of risk management for Paypal's newest, most innovative ventures, leading Paypal's growth in new markets and with new technologies. The role is for a leader of the seller risk aspect of new ventures, dealing with sellers and developers using our most innovative products. Note: though the position is titled "manager", this is not a people management position.
What I’m looking for is results driven, quick thinking do-it-alls who want to be involved with new products, markets and risk challenges within Paypal. You should have the passion for consuming a lot of data and information, be able to learn quickly and identify and define trends in concise terms. You should be analytical and with a quantitative approach but not a data cruncher without any understanding of the big picture – we are playing at all fronts. Know or be able to learn how to drive processes through other people and organizations; working in ambiguous situations and coping with change is a must, as well as an ever changing operating rhythm. This is not your classic 9 to 5 and I’m not your classic 9 to 5 manager.
Experience is not a must (=graduates are also encouraged to apply), definitely not previous experience in risk management. However, please be an avid internet user, preferably a gamer in your past or present. Some security experience or tech savvy is a big plus – don’t get intimidated by developers, architects and tech talk. Impress me by having interesting hobbies out of work that you maintain although you are an aggressive achiever, and by having vast general knowledge (as in: you shout answers at “who wants to be a millionaire” while watching it on TV).
Read the blog. Process. Understand. Talk to me.
Showing posts with label analytics. Show all posts
Showing posts with label analytics. Show all posts
Monday, March 8, 2010
Sunday, October 18, 2009
And now for something completely (?) different
I'm diverting from Risk per se the deal with another decision-automation question I'm wondering about.
High-tech fluctuates. It boomed on the verge of the new millennium, and did so (albeit differently) before the latest downturn. And when booming, help is required. High-tech companies don't usually post a "help wanted" sign on their office wall (though some in Israel did), and getting to a good position requires some work beyond coming from a good school. In the days of the "bubble", just knowing a few people would secure you a position somewhere in the space, but nowadays it takes a lot more than that - employers demand good grades, subject matter expertise and experience - all of which are no mere feat for new graduates.
High-tech fluctuates. It boomed on the verge of the new millennium, and did so (albeit differently) before the latest downturn. And when booming, help is required. High-tech companies don't usually post a "help wanted" sign on their office wall (though some in Israel did), and getting to a good position requires some work beyond coming from a good school. In the days of the "bubble", just knowing a few people would secure you a position somewhere in the space, but nowadays it takes a lot more than that - employers demand good grades, subject matter expertise and experience - all of which are no mere feat for new graduates.
Monday, July 20, 2009
Ain't doing it right
"How many legs does a dog have if you call the tail a leg? Four; calling a tail a leg doesn't make it a leg." (ascribed to Abraham Lincoln)
In our business, to make a good decision, it is essential to know what really happned. So we discussed finding the single source of truth, but have not discussed ways for keeping it truthful. Oddly enough, the concept of immediate, detailed feedback is not as common as one would expect.
In your community of domain experts, the concept of "truth" should not only be determined but also enforced by members of the community. Note: not by a moderator; the members must know what the "truth" is (in procedures, in decisions and in deriving conclusions) but also be ready and empowered to call out their and others' mistakes. Because direct feedback is what enforces people to improve in the specific of their work. You do not only need people who can tell a tail from a leg - you need to give the one who detects it the means to show their finding to the general community.
This is not a matter of virtue, it's a matter of getting your business runnig the way it should. What happens if you under develop this area in your organization? Well, first you get only hindsight feedback, allowing you to know what's happening in delays of months and months (how much time does it take 90% of chargebacks to come in? exactly), but you also get feedback in aggregate levels (saying, for example, how many of person X's decisions were reversed) - meaning that you can't really find the trend and fix it.
I can't tell you it's fun - commenting, moderating or acting on the results of such feedback cycles - but one thing's for sure, it's way more effective than pretending your Risk experts live in DisneyLand. Giving and receiving proper feedback improves every bit of the cycle - and makes your business better at one of its core competencies.
In our business, to make a good decision, it is essential to know what really happned. So we discussed finding the single source of truth, but have not discussed ways for keeping it truthful. Oddly enough, the concept of immediate, detailed feedback is not as common as one would expect.
In your community of domain experts, the concept of "truth" should not only be determined but also enforced by members of the community. Note: not by a moderator; the members must know what the "truth" is (in procedures, in decisions and in deriving conclusions) but also be ready and empowered to call out their and others' mistakes. Because direct feedback is what enforces people to improve in the specific of their work. You do not only need people who can tell a tail from a leg - you need to give the one who detects it the means to show their finding to the general community.
This is not a matter of virtue, it's a matter of getting your business runnig the way it should. What happens if you under develop this area in your organization? Well, first you get only hindsight feedback, allowing you to know what's happening in delays of months and months (how much time does it take 90% of chargebacks to come in? exactly), but you also get feedback in aggregate levels (saying, for example, how many of person X's decisions were reversed) - meaning that you can't really find the trend and fix it.
I can't tell you it's fun - commenting, moderating or acting on the results of such feedback cycles - but one thing's for sure, it's way more effective than pretending your Risk experts live in DisneyLand. Giving and receiving proper feedback improves every bit of the cycle - and makes your business better at one of its core competencies.
Tuesday, April 14, 2009
That one small detail
"When the Chinese government instituted the policy in 1979, it touched off a wave of sex-selective abortions as pregnant couples decided that if they could have only one child they would benefit most from having a boy. That helped leave modern China with the largest gender imbalance in the world. Today, there are 37 million more men than women in China, and many of the boys are growing up unable to find a job or start a family.
So what are these “surplus” boys doing to fill their time?"
This isn't just a story about risk management - it's a story of pure business intelligence - it is a story of freakonomics. The German police has spent years chasing down someone that turned out to be a phantom, a woman who wasn't really a feared killer in many different, distant crime scenes - but merely a lab worker whose DNA "slipped" onto the cotton swabs German CSI people used to collect evidence (on another note, wouldn't it be just morbidly funny if that person turned out to be a real-life German "Dexter" copycat?).
So what does an unsanitized cotton swab have to do with abortions in China, and with risk management?
When one approaches modeling of complex situations (either to explain what just happened, or to improve decision making in the future), often the "sense" made in the process gets deterred by the fact that not all the data is revealed. This is why when Freakonomics' author Steven D Levitt says something along the lines of "if we had enough data, we could unravel the mysteries of the universe", many of us nod (however, I must say, we are not always right); we are in constant search for the added detail that, when added to the equation, will help the story make sense. It's not only as extreme as claiming that a rise in abortions is correlated with a drop in crime rates - retailers are always looking for the additional factor that will verify a bank account, provide details for a phone number or do this automated super sophisticated AVS check. But fact is that most of the added data doesn't do the trick, since looking for that additional detail requires a system.
So what are these “surplus” boys doing to fill their time?"
This isn't just a story about risk management - it's a story of pure business intelligence - it is a story of freakonomics. The German police has spent years chasing down someone that turned out to be a phantom, a woman who wasn't really a feared killer in many different, distant crime scenes - but merely a lab worker whose DNA "slipped" onto the cotton swabs German CSI people used to collect evidence (on another note, wouldn't it be just morbidly funny if that person turned out to be a real-life German "Dexter" copycat?).
So what does an unsanitized cotton swab have to do with abortions in China, and with risk management?
When one approaches modeling of complex situations (either to explain what just happened, or to improve decision making in the future), often the "sense" made in the process gets deterred by the fact that not all the data is revealed. This is why when Freakonomics' author Steven D Levitt says something along the lines of "if we had enough data, we could unravel the mysteries of the universe", many of us nod (however, I must say, we are not always right); we are in constant search for the added detail that, when added to the equation, will help the story make sense. It's not only as extreme as claiming that a rise in abortions is correlated with a drop in crime rates - retailers are always looking for the additional factor that will verify a bank account, provide details for a phone number or do this automated super sophisticated AVS check. But fact is that most of the added data doesn't do the trick, since looking for that additional detail requires a system.
Yes, having a single source of truth helps give foundation, but even the brightest have a hard time without a system - and the right one at that - for collecting, validating and understanding data. I've seen this in organizations here and there and the German CSI story demostrates it well. The CSI department has a system for examining a crime scene and extracting evidence, and they came up with a concrete linking theory between cases. It didn't shed light on the actual identity of the misterious killer, however it gave an interesting spin to a bunch of unsolved crimes, until it didn't make sense anymore.
What the CSI department lacked was a key component of creating robust linking stories - indetifying common resources. That common BIN number in your last week's transactions might be a result of a data breach in the processor level, but might also be a result of a marketing campaign for a new eCard; and that repeated IP creating new accounts may be a script attacking your system but may also be a whole trend-struck fraternity house shopping through the same computer for that special item only you are offering for a great price. Noticing the trend, understanding it and making the right call on how to handle it are key decisions we are facing every day, and not only in eCommerce. Common resources are one simple example where correct classification, using an external resource, makes the difference between turning away good business and letting the fraudsters in; between chasing a phantom killer and tracking down a less-than-perfect lab worker. Using the right contructs for doing this is key in our ever-changing profession.
Subscribe to:
Posts (Atom)
