Jumping Rivers is a data science consultancy company focused on R and Python. We work across industries and throughout the world. We offer a mixture of training, modelling, and infrastructure support. Jumping Rivers is an RStudio Full Service Certified Partner. This role is suitable for anyone interested in deploying (Linux-based) data science services and contains

At Jumping Rivers we're always to want to branch into the data science community, and so this year we're going to quite a few conferences in the autumn. You can catch us at: GSS (Government Statistical Service) Conference - Edinburgh From the 1-2 October, our very own Esther Gillespie (CEO) and Seb Mellor (Data Engineer)

We're RStudio Trainers! Big news. RStudio recently started certifying trainers in three areas: the tidyverse, Shiny and teaching. To be certified to teach a topic you have to pass the exam for that topic and the teaching exam. Even bigger news. Four of your lovely Jumping Rivers trainers are now certified to teach at least

You'll be pleased to know that Jumping rivers are running R training courses up and down the UK, in London, Newcastle, Belfast and Edinburgh. I've put together a quick summary of the courses available through til the end of the year. They are sorted by place then date. You can find the booking links and

This blog post has two goals Investigate the bench package for timing R functions Consequently explore the different algorithms in the digest package using bench What is digest? The digest package provides a hash function to summarise R objects. Standard hashes are available, such as md5, crc32, sha-1, and sha-256. The key function in the

Earlier this month I attended the inaugural SatRday Newcastle. This was my first time attending a SatRday event, and I had a really enjoyable day. The event was sponsored by Newcastle University, Sage, RStudio and Jumping Rivers. There were over 100 attendees from across the U.K. Most attendees were from industry, although there were also

One of the great things about R, is the myriad of packages. Packages are typically installed via CRAN Bioconductor GitHub But how often do we think about what we are installing? Do we pay attention or just install when something looks neat? Do we think about security or just take it that everything is secure?

When discussing how to speed up slow R code, my first question is what is your computer spec? It's always surprised me that people are wondering why analysing big data is slow, yet they are using a five-year-old cheap laptop. Spending a few thousand pounds would often make their problems disappear. To quantify the impact

Jumping Rivers is a data science company based in Newcastle. We are not sector based and our clients range through all industries. We are looking for individuals who enjoy a challenge. Main Duties Technical Duties: Provide technical training Development of bespoke statistical algorithms. Building web applications using R and Shiny. Data analysis using R and/or