DLarsen
Joined 18 years ago
Karma
219
Submissions
154
Member since
Jun 17
engineer, data science, ML, RNNs, data viz, etc
View on Hacker NewsRecent submissions
Comment · 5 months ago
Location: Prescott, Arizona
Remote: Yes
Willing to relocate: No
Technologies: I've mostly built around data-heavy systems, and I'm familiar with the typical tools in that space. In this era, it's possible that my domain experience in adtech, rare disease and now IP/patenting is more interesting than the details of my tech chops. I have a pretty decent sense of how "analytics" or "insights" tools play out in the real world, and I know what holds up to scrutiny in decision-making scenarios. I enjoy early-stage projects quite a bit.
Résumé/CV: https://dataxam.com/larsen-resume-2024.pdf
Email: [email protected]
Note: I have a job, but as a father of five (incl. a bunch of teenagers), it pays to be risk averse.
Comment · 5 months ago
"Are (legally and morally) entitled" vs "act as if they are entitled"... yes, a big question.
Comment · 6 months ago
I've been thinking a lot about team formation and competence hierarchies in the age of AI. I'm particularly concerned about the disruption that occurs when performance and output outruns competence. In such a world, it's not obvious whose judgment to trust and how risk/reward should be allocated.
Comment · 2 years ago
I like the creativity of the new form factor.
My son and I are working on a spending journal which puts forth a new kind of form factor for tracking expenses. Our emphasis is less on the accounting angle and more on the behavioral side. We use the journal for self-evaluation of individual spending decisions and as a tool to communicate spending intent within our household. It turns out that between myself, my wife and our teens... not everyone naturally geeks out with spreadsheets, and this collaborative journal has been a decent middle ground to coordinate spending.
Comment · 2 years ago
I remember near the start of HashiCorp, Mitchell and I spoke about buying one of his side projects. In seeking to rustle up some funds, friends asked me why anyone would offload a profitable project at such a price. Mitchell essentially explained that he was moving on to focus on bigger and better things. Boy was he right.
Someone else beat me to the punch on buying the website, but Mitchell’s clarity of purpose was profound.
Comment · 3 years ago
https://spendlight.com
My 13-year old son and I have been working on a behavior-oriented personal finance tool. I've kicked this idea around for years, and we had a chance to use it as our subject for a 12-week entrepreneurial program. I built a version of it for personal use years ago, but had fun looking at it through the lens of a more serious endeavor.
It's not feature complete, but the demo of the SMS-based journaling input works pretty well: https://spendlight.app/demo
Comment · 3 years ago
MPP | SaaS-savvy Product Leader | Remote
Get in on the ground floor (2nd hire) of a new B2B, data-heavy venture.
We're looking for someone with hard-earned street smarts, and can help establish an outstanding working relationship between engineers (me for now!) and our subject matter expert (a 30+ year lawyer). Experience in finance, legal and data viz are a plus. A fruitful previous working relationship with DataSci professionals is a mega plus.
At the heart of our company, we seek to manifest a new business paradigm as usable (sells like hotcakes) SaaS. Big challenges, big potential reward, and (to shoot you straight) plenty of pitfalls on the product front that you can help us avoid.
We've got a good support network for both funding and advisors, all with legit unicorn-level chops.
Connect and message me at https://www.linkedin.com/in/larsenal/ to learn more.
Comment · 3 years ago
I think I'm going to start asking potential employers where they do their banking.
Comment · 3 years ago
Location: Prescott, AZ
Remote: Yes
Willing to relocate: No
Resume/CV: https://dataxam.com/about
Technologies: Python, SQL, R, dbt, Snowflake, Postgres, D3, Spark, Flask, HTML, CSS, Scala, Ruby, etc.
Email: david.larsen+hn [at] gmail.com
Mostly interested in nascent data product work. If your data asset strategy is critical to your organization's success, you'll find me to be a capable, thoughtful contributor.
Comment · 3 years ago
Integrating into the operations on a provisional evaluation basis is a whole lot of work and the stakes are high. As my grandpa used to say, "There's nothing easier than doing nothing." Both parties (our company and the airline) brought the right people to the table, but for the system to really be evaluated we needed an entire crew base to use the system in a "realistic" fashion. There was a fair bit of understandable skepticism about how the system would perform under the stress of real user input, but due to the overall complex nature of the system there was a non-trivial learning curve and lots of crew members didn't see a lot of value in spending their time help us put the thing through its paces. As an example, the system would allow crew members to specify a highly detailed, specific set of flight preferences that were either declared as ranked priorities and/or they could select specific flights. If a crew member was forced to "try" our system, they could put in a generic set of input ("I like the Vegas flight."). However, we suspected that once they were faced with the opportunity to share their real schedule, they would have a lot more incentive to put in a lot more particulars, which would stress our optimization engine differently.
Comment · 3 years ago
Does the algo work? Is it better than the status quo and under what circumstances is it susceptible to failure? Does it know when the whole system is over-constrained?
If we assume the algo rocks (because you have operations research veterans), what stage of planning does your system address? What is the experience required and cost of manual intervention?
Fun problem. Human factors and edge cases abound. So much is at stake for a system that already works (to any predictable degree).
I'd love to hear more though.
Comment · 3 years ago
We ran a pilot with one carrier for a subset of their crew for maybe a year, but eventually failed to gain further traction. Very tough sales and implementation cycle in spite of the fact that we could convince many individuals (bothe crew and management with their competing concerns) of the benefits of our system.
Comment · 3 years ago
About a decade ago, I was part of a startup trying to disrupt crew scheduling. It's a non-trivial operations problem when you aim to honor crew preferences, union-negotiated affordances, FAA legalities, etc. We were only involved in the pre-planned schedules. At that time, the airlines we were courting had entirely different human-hravybsystem to resolve real time issues. There was some level of reserve redundancy baked in so the human planners had some wiggle room to work with... but redundancy is expensive to maintain. As a relatively new engineer at the time it was a pretty neat domain with big $$$ at stake. As it turns out, pretty much nobody wanted to take the risk on a new system even if it had provably better schedules for all parties. All it takes is one snafu for the whole thing to turn into a major regret.
Comment · 4 years ago
Great feedback. There are several sample lessons, but from your feedback I see how I can make them easier to find.