naftaliharris

For what it's worth, I do believe that Python3 is a better language than Python2. We use Python 3.7 at my work (SentiLink) and we've had a good experience with it. (If you're starting a new project or can migrate, I'd recommend it). But I do think that the ~10 year saga of upgrading to Python3 from Python2 wasn't necessary when the main benefit was really the unicode refactoring.

I no longer maintain Tauthon personally but there are others who are excited about the project who occasionally add new features or bugfixes.

Comment · 7 years ago

SentiLink | Software Engineer (backend, platform, infra, machine learning, data science) | ONSITE | San Francisco, CA | sentilink.com

SentiLink prevents synthetic fraud, an emerging fraud vector in which fraudsters open accounts using name/DOB/SSN combinations that don't correspond to real people. Our partners include top ten US banks, fintechs, and alternative lenders. We're backed by investors including Andreessen Horowitz, Max Levchin (Affirm CEO/PayPal Co-Founder), and former presidents/CEO's of Visa, Transunion, HSBC, and Citi.

We recently closed a $14M Series A [1] and are hiring software engineers to help us build our identity platform. Our tech stack uses Go (for the API part) and Python (for the ML part) on k8s and the work involves a lot of complex and sensitive data.

Please apply at https://jobs.lever.co/sentilink.

[1] https://businessinsider.com/synthetic-fraud-detection-startu...

Comment · 7 years ago

SentiLink | Software Engineer (backend, platform, infra, machine learning) | ONSITE | San Francisco, CA | sentilink.com

We recently closed our Series A [1] and are hiring software engineers to help us build our identity platform. Our tech stack uses Go (for the API part) and Python (for the ML part) on k8s and the work involves a lot of complex and sensitive data.

Please apply at https://angel.co/sentilink/jobs or shoot a resume/github/linkedin to me, (my first name at a domain I'm sure you can guess).

[1] https://businessinsider.com/synthetic-fraud-detection-startu...

Comment · 8 years ago

Two super interesting things about this kind of fraud which make it especially tricky to catch and deal with:

1. Unlike with ID theft, there's no consumer victim. With ID theft, eventually the victim will find out about it, (by getting a call from a collections agent or seeing the trade on their credit report). They'll then contact the lender or the bureau, and contest the validity of the loan. The end result is that the lender gets a stream of loans that are labeled as identity theft losses. Since there's no consumer victim with synthetic fraud, though, lenders don't get this stream of labeled data and have a hard time knowing which of their losses are synthetic fraud (and which are just ordinary credit losses).

2. Synthetic fraud cuts right through typical ID theft prevention systems. ID theft prevention is about checking whether the applicant is the same as the identity they're using to apply for credit. So you check if the email the applicant uses matches the identity, (e.g. don't want [email protected] used as the email for Jane Smith), you check the phone number, you check if the applicant can complete KBA (knowledge based authentication, e.g. questions about previous addresses), you check the billing address, and so forth. But synthetic identities have their own aged phone numbers, emails, addresses, and credit histories, and so all of these verifications go through without any flags raised. Essentially the ID theft prevention system was checking whether the applicant is the same as the identity that they're using, but with synthetic fraud the applicant created the identity.

Source: my startup focuses heavily on preventing synthetic fraud for lenders, (PM me for details).

Comment · 8 years ago

SentiLink | Backend, Security, and Machine Learning Engineers | San Francisco | ONSITE

SentiLink is reinventing identity, beginning with financial services in the United States. The current system is broken: SSN's are used as both a username and a password, but after repeated data breaches are also effectively semi-public. Identity-verification data isn't shared, so the same fraudsters target every company and consumers have to continually reverify themselves with different institutions. Billions of dollars are lost every year to criminals who are very rarely caught or punished. SentiLink is building the arbiter of identity to bring identity into the 21st century.

Our investors include former co-founders and C-level execs at PayPal, Palantir, Affirm, Visa, and Citibank, including Max Levchin (SciFi) and Hans Morris (Nyca Partners).

Apply here: https://angel.co/sentilink/jobs or email me (first name at sentilink.com).

Comment · 9 years ago

It's pretty surprising students think they can get away with this. If there's any class you'd get caught in, it'd be a CS class. In the CS classes I took in undergrad and grad school, the professors would tell everyone they would be using automated plagiarism detectors, and even explain a bit about how they worked and explicitly say they were smart enough to detect the "rename-the-variables" trick.

That said, I've got to imagine that claims that "as many as 20 percent of the students in one 2015 computer science course were flagged for possible cheating" are a misrepresentation or a misunderstanding, on the part of the journalist. I mean, sure, if you set the threshold for the plagiarism detector at a low level, you can flag 20%, 50%, or however many students you want for "possible cheating", but it's not necessarily a real thing.

Comment · 9 years ago

Do customers not want to try out the bike before buying? Especially for $5k+...?