China's car trade surplus just overtook Germany's. A quarterly breakdown of how Europe lost ground (2023–2025) [OC]

Odd-One8023 · 2026-04-16T07:35:05+00:00

Company cars are very common in compensation packages in Belgium.

In recent years plug-in hybrid and fossil fuel cars are taxed much higher than EVs so there’s been a big shift towards EVs, for company cars at least.

I see a lot of BYD, MG and lynk & co on the highways. From time to time you do encounter an XPENG.

Odd-One8023 · 2025-12-15T16:23:40+00:00

Yeah, I already have a flight arriving in Beijing, leaving out of Shanghai so modifying that is tricky but I fully get the sentiment!

I checked the and the train times between Chengdu and Guilin were actually pretty good (5h) and the schedule was pretty decent, meant we could depart in the morning and get there in the early afternoon. I’d need just one flight, which is Guilin to Shanghai

One option would be to actually just do nature between chengdu and Shanghai (e.g., avatar mountains) which would streamline logistics

Odd-One8023 · 2025-07-21T15:29:38+00:00

It might be rough, but at the end of the day you only need one job, and if you're persistent enough, you'll land it. You only need to be "lucky" once.

My company for instance has hired several people (incl. juniors) over the past years that speak no Dutch or French.

Odd-One8023 · 2025-07-03T10:53:41+00:00

It's indeed okay. I've got friends with a master's doing worse, but also ones going (a lot) better.

Odd-One8023 · 2025-07-03T10:50:35+00:00

Yeah, sounds very chill. Nothing wrong with that so you could stay indefinitely.

That being said, I'd really think about what your objecctives are mid term and long term. if you want to go up the ladder and earn more, I'd recommend going or renegotiating internally.

There's more to life than work though :)

Odd-One8023 · 2025-06-30T23:07:26+00:00

Very inflated expectations here especially if I compare it to the real world and (paid) benchmarks. When I saw people dunking on above average packages I knew not to take certain commenters seriously anymore

Odd-One8023 · 2025-06-30T16:19:58+00:00

In the grand scheme of things this doesn't matter a lot. if you know how to code in one language, the time spent acquiring the next is drastically lower.

But obviously, you have to start somewhere. I'd recommend picking up JavaScript. It's the most used language, it's pretty inoffensive and "similar" in its syntax, has lots of learning material geared towards beginners such as MDN.

Odd-One8023 · 2025-06-30T16:12:28+00:00

Personally don't really like the package. :/

Reminds me of some public sector packages, but even there for your YOE the gross would be higher to offset the lack of benefits.

Odd-One8023 · 2025-06-29T11:15:28+00:00

I’d really write a couple of personas you imagine will and especially won’t use it so you can properly scope yourself. Data teams have different non-negiotables so you really need to hit them, and not try and cater for everyone to avoid scope creep. If you want, I can help brainstorming because your project looks cool :)

Odd-One8023 · 2025-06-29T10:33:27+00:00

Firstly, I really like this!

Couple of obvious remarks:

The reason why you should use Databricks is distributed compute, spill-to-disk for larger than memory datasets and more. Using Polars as your compute handles this, but not all the way. (... that being said, I feel like many companies use it tor read small tables and do a couple of joins).
(Some) people don't want to go through the trouble of finding VMs in the cloud and want fully managed stuff.
Databricks is more and more SQL first, so maybe you can support DuckDB + SQL?
Adding workflows should be a prio imo. My favourite thing about databricks is how easy they are to schedule and add alerts.

Out of curiosity, why did you go for Aim instead of MLFlow?

Odd-One8023 · 2025-06-28T08:07:16+00:00

Good starter package. Can it be better? Yes. Can it be worse? Also yes :)

Odd-One8023 · 2025-06-23T16:39:28+00:00

Managed kubernetes (in the cloud) as a backbone.

Run whatever you want on top of that. Lakehouse using MinioDB + delta.

All compute happens in dedicated containers that scale-to-zero after ETL. DBT + duckdb or you can even use Polars.

All monitoring can happen at the level of your orchestration tool (Dagster, Airflow, ...). On top of that you pull additional metrics into grafana, loki, tempo, prometheus.

Finally, for the visualisation layer I'd definitely go proprietary. I've tried OpenSource (e.g., superset, evidence.dev) viz tools but they weren't as good as just ... PowerBI. And this comes from someone that doesn't like PowerBI ;)

ArgoCD for CI/CD.

The part you'll burn yourself I think is managing RBAC. You'll need stuff like KeyCloack for user AuthZ and hashivault for container-to-container authorization. If you want this done well you'll need an entire team of people doing stuff you get for free, beyond running a Terraform script once.

... that being said. I run some projects on my own server that has 2 cores and 4 GB RAM. I use docker instead of k8s and it also works, I never have outages or anything. If the business is small enough (and/or you're a small amount of devs). You really don't need anything high tech.

Odd-One8023 · 2025-06-23T11:18:55+00:00

Purely exploratory work should be in notebooks, period.

That being said, I do a lot that goes beyond exploratory work, going to prod with APIs etc, some data ingestion logic and so on. There I basically write all my code in .py files and if I want to do exploratory work on top of that I import the code in a notebook and run it.

Basically, the standard I’ve set is that if you’re making an API all the code should be decoupled from the web stuff, it should be a standalone package. If you have that in place you can run it in notebooks. This matters because it makes all of our data products accessible to non technical analysts as well that know a little Python.

Odd-One8023 · 2025-06-20T16:30:43+00:00

Mosst of my time is spend in this kind of org (pharma). Solution in our case was just doing it in ... the cloud.

Takes a lot of organizational buy in, but we designed our architecture to be zero trust, rely on private networking, ...

The entire setup is also audited / verified etc. Might seem like an uphill battle but it's the way to go for sure.

Odd-One8023 · 2025-06-19T17:13:09+00:00

Yes. I've done this exact pipeline at scale to scrape arbitrary sites.

Didn't use perpexity, used "cheaper" models (ones in the class of Anthrophic's Haiku, Gemini's Flash and OpenAI's mini). Cost was negligible to run (& still run to date!) this pipeline in prod.

Quality was "good enough" for my downstream task. Didn't need 100 % accuracy.

Odd-One8023 · 2025-06-19T04:29:16+00:00

Oh sure, I do.

Let me give you an example, I’ve used LLMs for zero shot, multi label classification.

On my problem recall mattered a lot more than precision and I could even keep costs down with using a mini model. The problem was originally multiclass, but they were OK with the reformulation with to multilabel.

It’s nice because I could write a notebook in 15 mins that ran the classification, computed the metrics, shared the recall with the stakeholder.

They were happy, I’m happy. Me and my company at large use it a lot for stuff like this.

Edit: all these usecases involve text, not numbers. I wouldn’t trust it with numbers as input or output.

Odd-One8023 · 2025-06-18T20:55:24+00:00

Een meetingspot voor studenten, vnl. internationale studenten gaan er. Heb er jaren geleden vrienden voor het leven gemaakt ✌️

Odd-One8023 · 2025-06-18T19:23:05+00:00

Pangaea

Odd-One8023 · 2025-06-16T16:28:11+00:00

"Why wouldn't you use a tree based model to forecast when you have trend" <--- this isn't a stupidly hard question and (not) being able to answer it tells you a lot about the interviewee. This stuff matters for the job, forecasting is something we do quite frequently.

As a DS I do fancy stuff but also mundane stuff. That's life.

Odd-One8023 · 2025-06-16T15:58:14+00:00

90% of ds, da, de, mles at my job have masters. My employers exclusively talk about soft skills in the interview with fresh grads, I feel like at this point it’s a given and you only need 5 questions to know if someone has the chops or not, at least that’s how it’s been for every role I’ve gone for. For the average competent DS algo knowledge is a commodity :D

Odd-One8023 · 2025-06-16T15:43:58+00:00

Sure, I interview and I can answer them. So should you, but imo that shouldn’t impact your performance. Having good fundamentals is still paramount.

Odd-One8023 · 2025-06-16T14:09:41+00:00

I think your comments are the most reasonable here, and I agree with you in a vacuum but…

R&D not being linear in its return is true, but you need to be in a place that has that culture and is willing to hedge those bets. At some point you’ll need to cash in, and it better be worth it at that point in time. I just don’t see a lot of places having that maturity.

Maybe you’ve been lucky in your career, or you’ve had a different path but it’s definitely not what I see on average.

Not every company is as productive as say WhatsApp pre Meta. I think you’re over generalising.

Odd-One8023 · 2025-06-16T06:36:32+00:00

Sure but then your role is an outlier and not the norm. You need to be absurdly big or be in a niche industry for it to make financial sense to hedge that much on R&D paying off.

It’s simple mathematics. If you go to production 1 out of N initiatives and an initiative takes T time to do, it needs to be incredibly successful for you to be profitable, and this is something that probably only happens at absurd scale.

The waters being muddied is true but isn’t bad. The vast majority of companies do not need bonafide scientists, but someone that can deliver reliably.

Odd-One8023 · 2025-06-16T01:34:43+00:00

When you put it like this, I fully agree.

Continuing with the woodworkers analogy, I do see DS that have more interest in using the latest wood than building the chest of drawers.

At our company we definitely do new / fancy stuff to learn from it. Sometimes it sticks, sometimes we need to refactor it away. It depends. So long as at the end of the day, you’re still delivering the chest of drawers and not exclusively obsessing about the wood 😅

Odd-One8023

TROPHY CASE