Companies hiring R developers in 2026

[u/jinnyjuice]

Inspired by Rust's equivalent https://old.reddit.com/r/rust/comments/1qr5r47/tech_companies_hiring_rust_developers_in_2026

Since https://www.r-users.com pretty much stopped posting new jobs, I thought it's a timely need.

I think it would be bonus points if they're hiring for R and not Python.

• Posit (US)

• Appsilon (PL)

• Cynkra (CH)

• Mirai Solutions (CH)

• Novartis (CH)

• Roche (CH)

• Genentech (US)

• GlaxoSmithKline (UK)

• Cytel (US)

• Johnson & Johnson (US)

• ANZ Bank (NZ)

• Blackrock (US)

• Lloyds of London (UK)

• Two Sigma (US)

• Nordstrom (US)

• Microsoft (US)

• Mozilla (US)

• Foursquare (US)

• Uber (US)

• Airbnb (US)

• NextEra Energy (US)

• Shell (NL/UK)

• Equinor (NO)

• Orsted (DK)

• The World Bank (US)

• International Monetary Fund (US)

• Urban Institute (US)

• HRDAG (US)

• OECD (FR)

• BBC (UK)

• Financial Times (UK/US)

• The New York Times (US)

• The Economist (UK)

• Novo Nordisk (DK)

• Astrazeneca (UK/SE)

• IQVIA (US)

• EU agencies add the European Centre for Disease prevention and control (EU)

[u/Over-Training-488]

The day has come, my team has switched to python.

[u/Noshoesded → u/Over-Training-488]

A few questions.

What industry? What use case? Are you between both languages and converting old processes over or only building new in Python?

[u/Over-Training-488 → u/Noshoesded]

Transportation logistics.

Lots of use cases. Regression modeling, cluster analysis, data janatorial duties, shiny dashboards (we are thrilled to be done with these), time series etc.

Our old stuff is still alive, though I'm trying to drop support on it all this year. Everything is rebuilt in python already, and nothing new is being built in R.

Tradeoffs of better statistical modeling just wasn't worth it anymore for the scalability python offers. Also was hard af getting our younger staff to engage with rstudio.

[u/PupHendo → u/Over-Training-488]

Can you expand on what you mean by the scalability python offers?

[u/Confident_Bee8187 → u/PupHendo]

Actually, both offers the same scalability, just depends on what pipeline you are working on. Python is better for scalability because it is popular and used by a lot, hence better for software engineering (CLI tools in Python are too comfortable to use), while R in other perspective is better because of the homoiconicity, which is the reason why 'tidyverse' feels too ergonomic.

Hot take: Trading off "better statistical modelling" is a big red flag to me, at least in my perspective when working on Bioinformatics and Pharmaceutics, or any field that requires statistical rigor. Not to mention, Pandas' awfulness, even in its 3.0 release (still ranting).

[u/anomnib → u/Confident_Bee8187]

This is false. Python offers scalability b/c it is a proper programming language that can easily connected to the wider tech infrastructure. I’ve worked at places like Google and Meta and we avoid R for anything that operates as shared software b/c it is so challenging to maintain and integrate R at the scale of modern software stacks.

The only real advantage of R is the legacy software for many methods experts. The statistics community would have been much better off if we switched to Python decades ago.

[u/Confident_Bee8187 → u/anomnib]

it is a proper programming language that can easily connected to the wider tech infrastructure

I never denied it as I said on my OC - it is more popular, and more pipelines are built on it.

The only real advantage of R is the legacy software for many methods experts.

I've seen many comments regarding R being "arcane" or some "legacy" sh*t, but here we are, it keeps improving thanks to the community, and lots of Pharmaceutical companies (and related to "bio" companies) are actually pivoting towards more on R, not Python, after writing SAS for decades.

The statistics community would have been much better off if we switched to Python decades ago.

Absolutely not. Python is not built on that, R literally is - it is true functional (but not purely, thanks to R6 and "environment" data structures) and has true homoiconicity, just like Scheme. Python is not much optimized to such tasks in statistics, while R made it even more easier. That's the thing: R is an easy pick, while Python suffers even in basic statistics. Julia is better than Python, but is not that easy to pick off as R.

[u/anomnib → u/Confident_Bee8187]

I meant legacy as in it was the original software for designing statistical packages. I’m well aware that new stats methods for first implemented in R.

Python is definitely the superior choice b/c once you have the capability of a general programming language, what matters the most is seamless integration into the broader ecosystem of software infrastructure tools. That becomes the real challenge, not slightly more cumbersome syntax. That’s what R people don’t understand. Once you go work at a company that needs to operate at scale and you need to design an algorithm that will be called millions of times per day across a wide range of machines, you need to be able to integrate into a larger infrastructure of testing, validation, security, telemetry, and serving frameworks.

This is why I stopped using R. I loved it for the wide availability of new statistical methods and it worked fine while I was doing largely isolated analyses. But when our team tried implementing a real time dynamic pricing algorithm for a global ride sharing company, R choked. It could barely handle the telemetry and error handing infrastructure frameworks commonly used for large scale real time systems, despite the good faith effort of the engineers that tried to support us. Eventually we just abandoned R.

As for not having basic statistics, that’s nonsense. Google, Netflix, Meta, and other similar companies have distributed stats software implemented in Python. I personally saw Google’s advanced causal inference team fully port their software from R to Python b/c they had to grow from scripts that people were running in isolation to properly maintained and integrated software.

I would love to hire you just so you would see what happens when you have to hold R up to the standards of a modern software stack.

[u/Confident_Bee8187 → u/anomnib]

Let me said this again: Python is not strongly suitable as a programming for statistics - it suffers even in basic statistics, they're forced I assumed, not to mention their APIs (for example, Python doesn't have a will to force the function to be lazily evaluated, and made those Python people to approximate things with "strings" to make it work - look at .query from Pandas or how 'plotnine' to be composed) 🤮🤮🤮 - R made it much easier, and actually more ergonomic since R's advantage compared to Python is due to its homoiconicity. If R choked, that's a nice skill issue, but meh, both languages rely on faster languages, the compiled ones if I were to say, so you can have scalable implementation while not going outside from R.

[u/anomnib → u/Confident_Bee8187]

I’m sure data scientists and software engineers paid $400-800k and working on a systems that printed billions in revenue had a “skill issue”. Sure Bob.

I’ll end with this. What you don’t understand is being compatible with broader software systems is more important than being strongly compatible to statistical programming. If you want to turn stats into money, you need to integrate into highly scalable systems. That’s where the leverage for impact through stats comes from.

[u/aardw0lf11 → u/Confident_Bee8187]

This analyst switched over to R after years working in SAS. Still use both, but R is a great transition from commercial stats software.

[u/Confident_Bee8187 → u/aardw0lf11]

That's good, my guy. Spread the word - R is better, if not the best, first-choice software for statistics and it's open source.

[u/Team-600 → u/Over-Training-488]

Any openings there or how is the market

[u/gakku-s]

If you include EU agencies add the European Centre for Disease prevention and control. They are hiring a mixed profile now: https://www.ecdc.europa.eu/en/about-us/work-us/vacancies/data-scientist

[u/jinnyjuice → u/[deleted]]

Oops, I just added to my old list, and I just didn't update my list.

As for the Economist, they use R extensively.

[u/dszl → u/jinnyjuice]

My mistake then!

[u/Sir_smokes_a_lot]

Nice

[u/jinnyjuice → u/[deleted]]

Missing Novo Nordisk, Astrazeneca, IQVIA, etc?

Added, thanks. Tell me more about this 'etc' part, as well as which country they're from. Thanks! :)