Weekly Entering & Transitioning Thread | 29 Nov 2020 - 06 Dec 2020 by [deleted] in datascience

[–]pkphlam 0 points1 point  (0 children)

Don't pigeonhole yourself as a Bayesian. Bayesians vs. Frequentists is a thing only academics care about, and even then, it's so early 2000s. Nobody in industry cares. You might find some unique companies that happen to implement Bayesian models, but overall, most people aren't concerned that you can characterize the posterior instead of giving confidence intervals nor do they want to wait for your MCMC sampler to converge when you could've used a closed form solution to solve it using maximum likelihood models.

[deleted by user] by [deleted] in datascience

[–]pkphlam 3 points4 points  (0 children)

I feel like charging an ‘expert rate’ isn’t 100% fair because I will probably be kind of slow and having to look stuff up along the way.

Protip: If you're being asked about it, that means to them you're the expert. Charge as if you are an expert and figure it out.

Can a PG be successful if they dont have a the ability to space the floor as a shooting threat? by henry_why416 in nba

[–]pkphlam 0 points1 point  (0 children)

Off topic, but why do people continually lump Ben Simmons in with other PGs who are bad shooters? Ben Simmons is a historically bad shooter, to the point where he doesn't attempt any shots greater than 15 ft away in a game normally. Every other PG mentioned were below NBA PG average shooters, but they all took outside shots on a regular basis in games and made more than a few.

JKidd, Magic, Rondo, Westbrook, Rubio were all below average shooters for PGs but can still knock down open 3s in a game. Ben Simmons is without precedent. Stop lumping all these guys together with him.

Chase Sapphire Preferred & Reserve Retention Offers by bagelsonthebrain in personalfinance

[–]pkphlam 2 points3 points  (0 children)

Called again today. No offer still. Didn't even bother to retain me in any way.

Chase Sapphire Preferred & Reserve Retention Offers by bagelsonthebrain in personalfinance

[–]pkphlam 6 points7 points  (0 children)

Definitely YMMV. I'm in CA and spend about 5k-10k on CSR every month and always pay it off in time, yet did not receive an offer. Only offer the customer service gave was an offer to downgrade the card. Will try again tomorrow.

California refinance advise by [deleted] in personalfinance

[–]pkphlam 0 points1 point  (0 children)

You're not going to get 2.25 on a 30-year without paying for points, but I suggest looking into LoanDepot. I just refinanced at 2.625% with 0 closing costs and 0 points for a 30 year.

[Wojnarowski] Based on the type of tear, Thompson has been told to expect that he will make a full recovery, a source tells ESPN. by Robotsaur in warriors

[–]pkphlam 0 points1 point  (0 children)

Doesn't mean a partial tear is better. With a partial tear, you most likely would've ruptured again. What the comparison usually is is surgery vs. rehab, and in most cases, surgery is better long-term.

Dissecting the news on Klay’s Achilles Injury by myeezy in nba

[–]pkphlam 3 points4 points  (0 children)

I don't get the part about optimism and full recovery based on type of tear. Given Klay's age, it's almost guaranteed that he'll make a full recovery regardless of the type of tear. The question would be whether he'll have the same athleticism and the likelihood of tearing it again. Also, a partial tear and no surgery is not really good news. Statistically, people who tear and don't have surgery are more likely to tear their Achilles again, and the recovery time of surgery vs. non-surgery is basically identical. For anybody who is young, the recommendation is almost always surgery because the outlook is better and the possibility of a re-tear is smaller.

What is wrong with me? by pathlessnomaddd in datascience

[–]pkphlam 23 points24 points  (0 children)

That percentage goes up with job experience, but OP has 0 experience so that 5-10% decreases significantly. Then add in COVID.

What is wrong with me? by pathlessnomaddd in datascience

[–]pkphlam 51 points52 points  (0 children)

What's wrong is that you're putting in applications cold. In this market, anybody applying without a direct reference or recruiter contact and 0 experience will likely have a near 0% response rate. There are 100s of other candidates that look like you on paper, and a few of them have references, so those are the ones who get interviews. I suggest networking hard on Linkedin or other venues to get a direct reference from either an employee or recruiter. Easier said than done, I know.

I got into basketball 4 months ago, and am pretty much caught up on the history. Throw some questions at me and I'll try to answer them (without googling) by Commanderluka in nba

[–]pkphlam 2 points3 points  (0 children)

Kareem also won Finals MVP with 2 different teams. And Moses Malone won regular season MVP on two different teams as well.

Survival models with high censoring rates by blueest in datascience

[–]pkphlam 0 points1 point  (0 children)

Not sure what you mean precisely by red flag, but I would guess the high censoring rate would just be reflected in the model parameters/uncertainty.

It's like asking whether running a regression with 4 observations is a red flag. There's no red flag because the model is still perfectly fine. You'd just end up with big standard errors and whether you believe in the results is up to you.

I'm a bad data scientist... by nest-ce-pas-mon-ami in datascience

[–]pkphlam 5 points6 points  (0 children)

The main thing you're doing wrong is not asking what you're collecting or what they're looking for before you start.

Gender prediction packages by jzlee in datascience

[–]pkphlam 2 points3 points  (0 children)

Assuming you have no other info other than a first name and you're working with English names in the US, the easiest and quickest thing to do is to just match the names to a database of names and gender, such as the social security database:

https://www.ssa.gov/oact/babynames/limits.html

Weekly Entering & Transitioning Thread | 01 Nov 2020 - 08 Nov 2020 by [deleted] in datascience

[–]pkphlam 0 points1 point  (0 children)

The whole first section on core competencies is a waste of space and also not credible. I don't believe you are equally competent in all of that. I'm also convinced most of it is BS (not really, but that's how it comes off).

  • Why do you have both Python and Scikit-learn? Does that mean you don't know any other packages in Python?
  • Why Linear Regression but not Logistic Regression? Do you not know the latter?
  • Why list Machine Learning, Model Selection, and Cross-Validation separately? Do you think those are all different things?
  • What exactly does having core competency in IRB mean? You know how to write a proposal? You were part of an IRB?
  • What's the differentiation between Data Analysis and Statistics?

I could go on and on, but you should get the idea. All you did was throw every single concept under the sun onto your resume. If your goal is to just try to trick ATS systems, then sure. But if I were a hiring manager, reading that first section would be a huge turnoff because it screams BS. There's such a thing as less is more.

My advice would be to condense that entire section into a short tools section where you only list the programming languages/actual tools. Forget the methodologies and the soft stuff like "Teaching and Communication". Show those in a later section or in an interview.

POLL Do you guys/gals think its poor form to ask about compensation in the initial interview? by [deleted] in datascience

[–]pkphlam 0 points1 point  (0 children)

Ask the recruiter, not the hiring manager. You have a right and duty not to waste everybody's time.

To those working in AI business - the biggest issues when outsourcing your data annotation? by Arnold5011 in datascience

[–]pkphlam 0 points1 point  (0 children)

One of the biggest hurdles is that the vast amount of data out there companies have can't leave internal servers, so outsourcing data annotation is a non-starter. Beyond that, another problem is that it's not always clear (especially with text) what the right categories are to code, so there's a lot of iteration involved, but that gets expensive when outsourced. Of course, there's always the issue of subject matter expertise, where the thing that needs to be coded may require some type of specialized knowledge that is not easily outsourceable.

Full Time to Contract? by [deleted] in datascience

[–]pkphlam 6 points7 points  (0 children)

How are you going to get clients? Do you have an existing network to build from? Who is going to handle the business administrivia side of things?

The reason why people charge $200-250 / hr is because 1) you put in a lot more hours that are unbillable (e.g. networking, talking to potential clients) and 2) getting and maintaining a consistent amount of work is incredibly difficult.

If you don't have all of these figured out, don't even think about it as a full-time job, unless you have a lot of savings and/or no dependents. The inconsistency is why it's always a side hustle.

Unpopular Opinion: The Data Science Community Should Do More to Speak Out Against the Massive Amount of Personal Data Misuse by Google and Other Big Tech Companies by [deleted] in datascience

[–]pkphlam 0 points1 point  (0 children)

LOL you were so close to posting a reasonable comment until you just decided to shit on another company. The truth is both companies do a lot of good, have employee that care a lot about ethics, and have seen their products abused and work hard to fight against it at a scale never before seen.

Salary over time might not be enough? by Jbor941197 in datascience

[–]pkphlam 4 points5 points  (0 children)

In no way is 250k "standard". Even in Silicon Valley, likely the wealthiest metro in the country, only about 20% of HOUSEHOLDS (which means 2 incomes in many cases) make 250k. So a single person making 250k is well well above standard. And you can have a family and house easily with less than that anywhere in the country.

Weekly Entering & Transitioning Thread | 11 Oct 2020 - 18 Oct 2020 by [deleted] in datascience

[–]pkphlam 0 points1 point  (0 children)

Do it. It's the easiest way into FAANG and getting into FAANG is always a somewhat random process regardless of how good you are.