Services

Here are some examples of the kinds of projects I work on:

Designing and Building Internal Data Tools

Many of the previous projects I’ve worked on have focused on getting value out of existing data and building tools to help people make decisions or automate workflows.

This could be:

a Shiny app
an automated report or dashboard
an R package
an API for connecting data science outputs with other systems
something else entirely

I’ve worked on projects which have been rolled out to the NHS, large scale open source projects, and internal tools for automating slow and manual processes.

My approach focuses on building something that delivers clear business value aligned with your goals, and is usable and supportable, not just technically functional.

Strengthening R Code for Production Use

Data science is distinct from software engineering in the approach to creating data products and tools which best support the needs of an organisation; the development cycle is often much faster and tends to be supported by domain experts whose skills skew more towards the interpretation and use of the data, or complex modelling.

This can mean tools which are effective to get a process off the ground need additional work to ensure that they remain efficient, reliable, and maintainable as they scale to more business-critical usage or more users.

Sometimes this is as simple as ensuring code is well-tested and contains all the checks and oversight to ensure confidence in the output it provides.

Other times, this might require more extensive refactoring, including things like:

simplifying overcomplicated code and implementing best practices to reduce time and money spent on maintenance and lowering the barrier to entry for those working with it
setting up CICD pipelines to automating the testing and building of code and reduce or remove manual effort
implementing software engineering practices like logging, versioned release strategies, and dependency management to ensure reliability and integration with other tools

I can help transform your existing code into robust production-quality tools, taking a practical approach which accounts for where you are now, where you want to get to, but most importantly how to get there in a way which will be sustainable in the long-term without overcomplicating things.

Planning and Delivering Migrations to R from SAS, Stata, or Excel

Working with open source tooling like R has huge benefits like reducing or removing dependency on expensive proprietary solutions, allowing greater flexibility in what you can do with your data, enabling reproducible workflows, and being part of a huge community of practitioners that you can learn from and benefit being part of.

Migrating from existing tools can present some challenges though - working out how to translate functionality from an existing legacy tool to R and reaping the benefits while minimising disruption.

Some of the ways I can help with this transition include:

upskilling new R users in R basics, focusing on the skills they need to do their job
analysing legacy codebases and helping you plan the transition to R
creating R packages, Shiny apps, and other data products to replace previous workflows
providing training and mentoring on R best practices
designing and implementing processes for managing internal codebases in a sustainable manner
and more!

Every code migration is different, but I can help you take this step, focusing both on the technical side of things as well as the people aspects - which are just as important but easily overlooked!

General R Consulting and Team Support

I’m also available for more general R and data science consulting and team support. Whatever it is that you need, feel free to get in touch, and we can see if I can help you, or refer you on to other wonderful folks I know in the wider R and data science ecosystem.

Take a look here to see some of my previous projects, or visit my contact page to get in touch.