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> My heuristic when evaluating potential jobs is only to consider positions where the output of statistical analysis and machine learning models has a clear and

> My heuristic when evaluating potential jobs is only to consider positions where the output of statistical analysis and machine learning models has a clear and immediate impact within the organization, while avoiding adtech for ethical reasons and because of concerns toxic work could enable a toxic environment. Currently starting to look for a new role and couldn’t have articulated my goal more clearly. The problem is that this narrows the field considerably, to finance/insurance/fraud (“pure money work”), healthcare/EMR (which as far as I can tell is also actually just profit optimization work for hospitals), and then you have manufacturing (closer to where I currently am), but the actual applications of data science are more limited and data Eng / analytics are more valuable, bioinformatics (which is really interesting, but also a large learning curve), and then just traditional BI (kind of generic and boring). Also, if you’re thinking about long term career development, many of these functions fall under the IT/CIO umbrella as orgs grow, which means that career advancement would require learning cloud architecture, cybersecurity, IAM, networking, etc. which I’m not saying is a bad thing, just an observation. Just applying statistics and modeling can only rise so high in an org, unless like you said, their core business and value prop is being the best at modeling some phenomena.

skrtskrt 4y ago
anti-fraud is very unsexy work IMO, but as long as you believe that (insert some internet-enabled service) should exist, then it can't be safe and enjoyable to use without serious fraud mitigation and prevention work, you can be secure in knowing that you're making life a lot easier for people who otherwise would have suffered from that fraud
- bglazer 4y ago
  Curious why you think antifraud is “unsexy”? I worked in the field for a few years. My experience was that the bulk of fraud is easily detected with bog standard models (most people doing fraud are lazy). But, there’s a long tail of super sophisticated work for detecting more subtle operators. It’s also pretty fun to learn about the convoluted schemes people come up with for doing fraud and to imagine how someone would attack a new service. Also theres quite a bit of money sloshing around and it’s relatively easy to quantify financial benefit from fraud reduction, so the departments tend to be well funded
  - skrtskrt 4y ago
    unsexy just in that it's not like a net new feature thing you can point a random person to like "I made that!" Like security, it's a field where success is when (externally) no one knows anything ever happened.
getoffmycase 4y ago
I’m finishing my bioinformatics-centric PhD and I really resonated with the author’s sentiments. Except in the case of the bioinformatics field, I feel like there’s too much data for any person to make sense out of. And if you do anything beyond a volcano plot, everybody’s eyes roll back into their head and they get bored and ask for their volcano plot or their special gene/protein/transcript of interest. Tbh I dread my future job of maintaining R and python scripts
munchbunny 4y ago
> which means that career advancement would require learning cloud architecture, cybersecurity, IAM, networking, etc. I was going to suggest: we have a bunch of data scientists working on intrusion detection problems in cybersecurity, tied to an engineering organization instead of an IT organization. On the balance of considerations, I think it has a net positive impact. And I'm pretty sure plenty of other companies have something similar. Unfortunately, we also have an ongoing hiring freeze, so I can't recommend my own organization.

skrtskrt 4y ago

anti-fraud is very unsexy work IMO, but as long as you believe that (insert some internet-enabled service) should exist, then it can't be safe and enjoyable to use without serious fraud mitigation and prevention work, you can be secure in knowing that you're making life a lot easier for people who otherwise would have suffered from that fraud

bglazer 4y ago
Curious why you think antifraud is “unsexy”? I worked in the field for a few years. My experience was that the bulk of fraud is easily detected with bog standard models (most people doing fraud are lazy). But, there’s a long tail of super sophisticated work for detecting more subtle operators. It’s also pretty fun to learn about the convoluted schemes people come up with for doing fraud and to imagine how someone would attack a new service. Also theres quite a bit of money sloshing around and it’s relatively easy to quantify financial benefit from fraud reduction, so the departments tend to be well funded
- skrtskrt 4y ago
  unsexy just in that it's not like a net new feature thing you can point a random person to like "I made that!" Like security, it's a field where success is when (externally) no one knows anything ever happened.

getoffmycase 4y ago

I’m finishing my bioinformatics-centric PhD and I really resonated with the author’s sentiments. Except in the case of the bioinformatics field, I feel like there’s too much data for any person to make sense out of. And if you do anything beyond a volcano plot, everybody’s eyes roll back into their head and they get bored and ask for their volcano plot or their special gene/protein/transcript of interest. Tbh I dread my future job of maintaining R and python scripts

munchbunny 4y ago

> which means that career advancement would require learning cloud architecture, cybersecurity, IAM, networking, etc. I was going to suggest: we have a bunch of data scientists working on intrusion detection problems in cybersecurity, tied to an engineering organization instead of an IT organization. On the balance of considerations, I think it has a net positive impact. And I'm pretty sure plenty of other companies have something similar. Unfortunately, we also have an ongoing hiring freeze, so I can't recommend my own organization.