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I know there are already a few "Who Is Hiring" aggregators, but I wanted to show off what I've done. My project was cancelled right before Christmas, so this project was a great way to blow off some steam while procrastinating looking for a new job. Tangentially, I am looking for new career opportunities if your company needs a full stack web developer, lol.
This website was completed in about a week and a half. I wanted to present it in a Show HN post on Jan 2 when the usual Who Is Hiring posts were featured, but I didn't think it had enough features to make it useful. Even this version has minimal features, such as adding personal notes and marking jobs as applied.
There's some other features I want to add, specifically advanced filtering capabilities to see new posts since your last visit, hide posts you're not interested in, saving search patterns as custom filters, and adding support for AND/OR logics in search patterns.
The frontend is a reactjs application being served on a basic AWS S3 website with CloudFront in front of it for HTTPS capabilities. The backend API services is a nodejs application running in an AWS Lambda function hooked up to AWS API Gateway. Who is hiring data is refreshed every 15 minutes in a separate Nodejs Lambda function from https://hn.algolia.com/api. The data is saved in an RDS, which is the largest monthly expense. This could be replaced with Aurora Serverless in the future.
Critical feedback for any and all aspects of the project is welcome. If you have feature requests or want to contribute, let me know here or file a GitHub issue.
https://www.whoishiring.work/
https://github.com/jerroydmoore/whoishiring.work
Thank you for your time!
Any job boards you can recommend?
http://mydataorganizer.com/ycombJobsMay2012.html
Please provide feedback.
Thanks,
Neal
Here's the code used to scrape HN API, kinda hacky: https://github.com/bfung/HNAnalytics
Here's the data and the a chart on [google sheets](https://docs.google.com/spreadsheets/d/18kLWHkrEedpl1eXzAht_se8GEKd0G9zrlz7SutP2uLQ/edit#gid=846434603)
A few things stick out: Dec and Jan are low job post months, as it makes sense due to holidays and fiscal cycles, and it shows in the # of posts.
Hope this helps would be job hunters in preparing for the next few months.
Inspired by an insightful comment on a previous thread (https://news.ycombinator.com/item?id=36163021), I built a tool that aggregates job postings and intelligently categorizes them based on user-specific preferences:
* Country and remote work preferences
* Employer type (e.g., startup, corporation, government)
* Industry
* Technologies used
* Role type (developer, architect, product owner, etc.)
* Salary range (where available)
One of the superpowers of LLMs is reformatting information from any format X to any other format Y.
We leverage this to map all the unstructured job postings into the same unified structure. The new GPT functions feature and the extended context windows are really helpful for this.
Instead of having to build a custom NER pipeline, it works very well with GPT out-of-the box.
One challenge is keeping the filters consistent and merging of duplicates. Embeddings help with that.
What's next:
* Integrate additional sources. We can generate web scrapers and data processing steps on the fly that extract and transform data into the same structure.
* Add location distance filters.
* Expand beyond jobs to monitor personalized data like events or real estate. Imagine using AI to rate local events from multiple sources based on your preferences, considering factors like your interests and distance from home.
* Smaller improvements based on your feedback :)
1/ Asked from young-ish developers, so the expected answer is always less than 18.
2/ Asked in addition to coding/system-design questions.
Has anyone seen a study or even an anecdote on correlation between success of a developer if they started coding earlier (say 11yr), rather than later (say 15yr or 16yr) in their youth?
Like, I would be curious to know, when you send out an application to a job that is at least a reasonable match, what percentage of companies do you actually hear back from? ("Hearing back from" defined as, you get a rejection email, or they contact you for more info or an interview/screening call; but NOT the automated mails some companies send to let you know they received your application.)
I would also like to know things like:
- how many of such applications lead to an interview vs instant rejection
- how do these percentages compare to places like Dice, StackOverflow, etc, or just "non-HN" or even "all applications to anybody"
I am keeping some stats about this myself, although not as detailed as I would like. As of today, I have been hearing back (in some form or another) from about 51% of applications to HN job postings. This is a bit higher than for the total number of applications, which is currently at 42%.
Anyway, I am curious to hear if anybody else keeps similar data.
also would be interesting to eke out comp trends over time but it seems the submitted data is still so unstructured that its unlikely to yield useful results.
After reading Part 1 of the Hypermedia Systems book [0] I wanted to see if I could make an interactive data viz with just HTML and CSS.
Here is the initial result which shows a technology adjacency table for job openings posted to the Ask HN: Who is Hiring? thread (May 2024)
https://ludicrousdisplay.github.io/HN/whoishiring202405.html
Rows and columns correspond to one or more related technologies. Values in the table show the number of job postings that mention the technologies corresponding to the cell's given row and column.
Clicking on a row header or table cell will display a list of matching job postings. Clicking on the text in the top left corner of the table displays the job postings that do not reference any of the technologies in the table.
This is a first step, proof of concept, so I'm interested to hear people's thoughts on the approach. I plan to produce another viz for the June Who is hiring? thread towards the end of next week.
I'm excited to share this little project with you, made possible by ChatGPT's "My GPTs" feature.
I've just created a GPT assistant that can assist you in discovering job opportunities from the "Ask HN: Who is hiring?" thread for November 2023.
If you're curious about the process of collecting and standardizing the data, you can find all the intricate details at https://bulkninja.notion.site/Converting-Ask-HN-Who-is-Hirin...
The next step was a breeze: I simply created a new GPT instance and uploaded the data as a JSON file.
Enjoy exploring job prospects with this GPT assistant!
One of the chief complaints I see on HN is that there seem to be a number of postings on "Who Is Hiring" where the emails listed don't see to be very responsive.
I'm wondering if it's possible to build something that works similarly to Mixmax's email tracking, but for groups. The stats for a specific job post email could be stored at a url that would be generated from something like the hash(username+email listed+datePosted) or something of the like.
When emailing a job posting, if everyone included something like this, it would give a huge amount of data about which emails were responsive or not.
I wanted to ask those who know more about how Mixmax does this whether this is even possible--my understanding here is really limited to plugging in Amazon SES for startups; and I don't use Mixmax. Just wanted to float the idea out there, and fully expecting that it's not a great idea or not feasible, but just wanting to hear feedback.
We are Pascal and Beroli, co-founders of Voorjob (https://www.voorjob.com) a small startup from Copenhagen that is going to help you get a new job from today's Who is hiring thread.
We started sketching this idea while I was looking for a new job opportunity at October's thread. During the job search I went thought a process that might be familiar to many of you: sending dozens of resumes, writing custom cover letters, having interviews, getting ghosted, the whole nine...
That was when we realized one thing: Today's hiring process with all those fancy ATS, resume parsers and ML algorithms, is kind of broken, the power is almost entirely with the side that is hiring.
We decided to fight back!
At first we are trying to solve the data manageability of job hunting, our initial set of features encompasses a few tools that will help you thought this journey: backlog of applications, application manager, assets (resumes and cover letters)
In addition to the management/tracking features, you get insights! Find out which cover letter (or resume) is working better, you can track variations for different positions, learn your bounce rate, your conversion rate and get to know where to focus your efforts. And that is just the beginning, we have a backlog with 100's of new features and improvements, and we hope to prioritize and grow it from your feedback.
One of our early users, agreed to share his job stats with the HN community so you can peek a look at what kind of information our product provides: https://www.voorjob.com/app/link/6da0ba76-e753-4012-95fd-53409e6ab78c/
Since everyone here has probably hunted for jobs before, we would love to listen your feedback and learn more about the pain points that you think we should be focusing next.
Happy hunting!
[1] https://news.ycombinator.com/item?id=21612151
[2] https://news.ycombinator.com/item?id=13783786
[3] https://news.ycombinator.com/item?id=14729005
Pre-launch data infrastructure startup is
hiring founding engineer
Very curious.. what on earth is going on here?
What is wrong with this picture:
Founders of an infrastructure startup are hiring a "founding engineer".
Am I the only one who believes this to be likely be a poor way of going about founding an infrastructure company to be laughable?
What value are the founders adding if they aren't experts in the domain the company is entering?
At Barracuda, we make the world a safer place. We protect email, networks, data and applications with innovative solutions that grow and adapt with our customers’ journey.
We know a diverse workforce adds to our collective value and strength as an organization. Barracuda Networks is proud to be an Equal Opportunity Employer, committed to equal employment opportunity & equitable compensation regardless of race, gender, religion, sex, sexual orientation, national origin, or disability.
Engineers interested in developing innovative security solutions, please look to Barracuda for career opportunities.
Follow the links below to learn more and apply today.
Backend Engineer: http://jobs.jobvite.com/barracuda-networks-inc/job/ohjvgfw5
- Staff Software Engineer (Platform)
- Software Engineer (Platform)
- Software Engineer (Imaging)
About us:
Oncora is an oncology software and data company dedicated to helping physicians and scientists collect and use real-world data to improve outcomes for cancer patients. Our products include: a workflow integrated data capture software system for radiation oncology, a data warehouse to amass real-world, regulatory-grade oncology data, a predictive model API with machine learning algorithms to power partner software, and a life sciences partner product leveraging automated medical image analysis to advance new technologies in the fight to cure cancer. We work with world-leading cancer centers such as MD Anderson and Northwell Health, and our team is mission-driven to its core.
We are looking for an experienced engineer to join our mission driven team to help develop our data platform that integrates and transforms multiple imperfect and messy data sources into clean, usable data so that we can learn from every cancer patient.
Learn more here: https://oncoramedical.com/careers/
A year ago it was 0.23. Here's a plot with the data from the past couple of years - https://pasteboard.co/tjZd0PgTI8GK.png
(posting this about a day after the April thread opened)
There are ways to read HN other than this website. However, I have not found one that meets all of these requirements:
- Self-hosted.
- Offline access of data.
- Query data via SQL.
- Full text search of stories and comments.
- Notification of replies to comments.
Some ideas:
1) A tool that maintains a copy of the HN API[1] in an SQLite database, with indexing and full-text search[2]. This supports the development of the other tools.
2) A command line tool that demonstrates how to use the database and supports the development of scripts. For example:
#!/bin/sh
# Run notify whenever someone replies to a comment.
$ hn replies username | notify
3) A web UI for browsing and searching. This can be hosted locally or on a remote server.
What features interest you?
[1]: https://github.com/HackerNews/API
[2]: https://www.sqlite.org/fts5.htmlAs a senior eng/data scientist who is looking for a job change it is extremely frustrating to apply to every interesting job posting and spend 30 minutes in a conversation just to find out that they are not willing to pay more than what I currently earn.
This topic is so sensitive and wrapped under secrecy that there are multitudes of blogs, sites dedicated to teach people negotiate and reveal this information. I'd think putting salary ranges outright would even benefit hiring managers first attracting correct candidates and also saving their time.
otoh senior guys, while changing jobs how do you ensure that you only interview for the companies that provide better compensation than the current one.
As a former startup founder, lately I've been facing the complex challenge of transitioning back into the traditional job market. With no experience in the job searching game for the last 10+ years, I had no idea what I was getting myself into
I still have a lot to go, but one of the most annoying and time-consuming parts of the process of applying to jobs so far, has been just even trying to find the right jobs to apply to
Every jobs site has hundreds or thousands of jobs, they are usually hard to filter. Then when you get the results, you still have to spend a lot of time reading and scrolling through the listings, figuring out which ones are good matches and which ones are not
Even here in HN, every "Ask HN: Who is hiring?" post has hundreds of listings (the February one has 300+ job posts). Reading through them all can take hours, which is super draining. By the time you are done reading, you are almost out of energy, and you haven't even started applying yet
I just wished I had a database where I could do something like:
SELECT summary, why_is_a_good_fit, how to apply, link FROM hn_jobs
WHERE remote AND use_ruby AND good_fit
So, I built it. Well, I wrote a couple of python scripts that:
* scrape an "Ask HN: Who is hiring?" post
* processes all the listings with GPT
* saves all the data in a sqlite3 db
It takes a few minutes to run the whole thing and populate the db (for each listing, a prompt is sent to GPT with questions, a resume and the job listing, GPT returns a json object with answers that get stored in the db)
But after it's done, I can get the absolute best matches for my own resume in seconds
With each result, I get the information about the listing, as well as why it is a good fit for me and instructions on how to apply (including link and or email address)
So far I've probably put more time into this than I've saved (surely there's an XKCD comic about this), but hopefully this hasn't been in vain and my loss can be your gain. That's why below I'm sharing links to the scripts. Please feel free to check them out, use them and modify them to fit your own needs
There is a lot of space for improvement, especially building and tweaking the prompt, which is one of the most challenging things to iterate on. If you try the scripts, make sure to modify the included sample resume, the questions asked and checking that the sample json output structure matches your questions
-> Would love to hear your feedback, suggestions, and also stories about your recent job searching experience in tech!
Thank you
Links to scripts:
* get_ask_hn_jobs.py: gets job listings from HN (make sure to adjust the base url of the "Ask HN: Who is hiring?" page to scrape) - run this first to populate your local db - https://gist.github.com/nicobrenner/88cc2aaf4fde7cbb119c6ca67fd50bc2
* ask_gpt_job_listings.py: enriches jobs listings from db using GPT (you need to add your own OpenAI API key, make sure to modify these variables: resume, roles, ideal_job_questions, prompt, and also check that the sample structure of output_format matches your prompt/questions) - run this after running get_ask_hn_jobs.py - https://gist.github.com/nicobrenner/dc1e6968dcd396c6367a63ac4c61f5d3
* filtered_job_listings.sql: query for sqlite3 db that gets best job listing matches - you should tweak the query to filter according to your preferences - https://gist.github.com/nicobrenner/f8da15c99c45c229c03c89dae1ed94d6
In one of the technical interviews the developer asked me to write a program to find Big O complexity of a given program. I asked about the input constraints to check if this was for recursive functions only and got a reply "all code in the universe, including the code for the program itself".
I explained to him about Halting problem and why a solution was not possible and also explained I could write a program that uses master theorem to solve a recurrence relation for those that fit the theorem.
He farted and said that's how much my answer stinks. It was pretty rank, enough to peel the wallpapers in the room. I said thanks for the feedback, got up and left the building. On my way out, I emailed the recruiter and politely stated that I do not wish to interview with them any longer.
Two days later I got an email from them stating they're not going to proceed with my application as the developers expected me to be more knowledgable about complexity analysis and data structures.
This got me thinking, why are technical interviews one-way? For a nine round interview process, why don't we kick it off by having their best engineer fight me in a 1 v 1 code battle?
I have some free time, and I would like to know how can I start finding these jobs.
I tried using ODesk, but unfortunately, the level of projects submitted by most clients is vague (without clear milestones), in addition to that the level of price competition is very low (for someone living in expensive city). I tried also "who is hiring", but most of companies look for full-time employees, not seasoned data engineerS/data scientists, who can work on part-time projects (approximately: 5-4 hours a day).
Please, share your experience with us ?
I would like to validate on an idea I have been wondering about.
I am extremely passionate about programming, web development (backend), smart financial and business applications and data analytics.
However, I do not have a CS mayor (I studied economics) and I do not have enough experience to apply for software development junior positions. Another problem is that I live in Europe in a city with no startup/IT culture. Around me I only see .NET developers and SAP consultants and no such things as Code Academy or HN meet ups. Also, I have limited time as I work full time in controlling/finance.
An example of position that would interest me: http://www.readyforzero.com/jobs/backend-engineer.
So, lately, I have been thinking that I could work for free on week ends and, if the potential employees mentors me, that I could learn enough in 2 or 3 months to be hired as a junior. I think I can learn so fast because I already know the basic concepts, I programmed in python and R to analyse pricing in a medium company and now I am building a small analytical tool in clojure.
I see this as a win win situation. The potential employer gets some free work and the chance to know deeply who he is hiring (if he decides to hire, of course), I get the chance to accelerate my programming learning and possibly relocate to a part of the world where people actually have a start up culture.
What do you think? Comments, advices? If you think this is a good idea, how would you go with implementation? Web site and post on HN? Other ways?
Thanks!
https://techcrunch.com/2015/03/21/the-terrible-technical-interview
https://medium.com/lightspeed-venture-partners/most-tech-interviews-suck-the-only-4-questions-that-matter-1a71181ef4d4
Numbers are total comments and estimate is >90% of comments are job posts. Summary: February 2023 comments are less than half of the peak in 2021 when several months had >1000 comments.
2023: 2/23 = 465, 1/23 = 533
2022: 12/22 = 576, 11/22 = 635, 10/22 = 560, 9/22 = 618, 8/22 = 761, 7/22 = 617, 6/22 = 852, 5/22 = 844, 4/22 = 798, 3/22 = 869, 2/22 = 883, 1/22 = 766
2021: 12/21 = 832, 11/21 = 1019, 10/21 = 852, 9/21 = 968, 8/21 = 907, 7/21 = 987, 6/21 = 1041, 5/21 = 925, 4/21 = 970, 3/21 = 964, 2/21 = 1052, 1/21 = 848
2020: 12/20 = 767, 11/20 = 808, 10/20 = 811, 9/20 = 698, 8/20 = 828, 7/20 = 681, 6/20 = 659, 5/20 = 686, 4/20 = 601, 3/23/20 = 786, 3/20 = 776, 2/20 = 677, 1/20 = 697
2019: 12/19 = 673, 11/19 = 742
OpenAI employees, watch for this flood of ChatGPT prompts:
how to gamble on stocks with HN hiring data?