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At Mango, we firmly believe that any decision can be better made using analytics and data. We also know that a company’s success is increasingly dependent on becoming data-driven. That’s where we come in. Our mission is to empower organisations to make informed decisions using data science and advanced analytics to drive bigger gains, lower costs, and optimise performance.

If this inspires you, read on!

We love nurturing new talent, so we are looking for graduates to take on this coming September to join our awesome team.

What we’re looking for

  • A degree in a STEM subject – and some knowledge of statistics and programming
  • The ability to explain complex topics simply
  • Most importantly you need a real interest and curiosity in data and the value that can be gained from it

We will help you build the required competencies and behaviours suited with a Mango data science/engineering consultant.

Entrants to the graduate programme will be expected to participate in a range of activities, including:

  • Mango’s world-class technical training (roughly two courses per month)
  • Soft skills training, including our ‘Trusted Consultant Program’
  • ValidR development and package building/validation
  • Delivery and presentation of a mini project showcasing existing and learnt skills
  • Shadowing various other parts of the business – e.g. teaching, sales, project management
  • Attending conferences – e.g. Bristol Data Science, LondonR, EARL
  • Google Certification
  • Contributing to client-focused projects as skills and approach reach the required level

If this sounds like the role for you then contact us.

 

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What’s in a Data Community? One of the UK’s top retailers, Sainsbury’s, knows just how much value can be derived from a community, which, when coming together in a data science context, can add immeasurable business benefit throughout the organisation.

In fact, Sainsbury’s firm belief in the power of data science and community has led to the establishment its own Data Community, which collaborates with teams across the business to find new ways of working with data and learn what’s possible. Part of the activity includes biannual Group Data Conferences, which provide an opportunity for Sainsbury’s 800-strong community to come together to listen to inspiring ideas, connect as a community and get involved with all that the industry has to offer.

As big believers in data analysis that delivers, the Mango team was thrilled to be involved with the company’s most recent Group Data Conference, delivering two R-focused workshops; a high level Introduction to R for analysts not familiar with this popular statistical programming language, showcasing why R is one of the leading data science tools, and a Package Building in R workshop for more advanced users that focused on getting started with building packages, understanding the benefits of package building best practices and being able to implement them.

“We were delighted to have Data Science experts Mango Solutions participating at our internal LOVE Data conference – an event for the 800 data professionals across our Group,” said Naomi Sayers, Sainsbury’s Group Senior Manager of ADS Community & Capability Group Data. “Mango provided training workshops, supporting our aim of inspiring and connecting our community.”

Mango has and continues to support various large companies and organisations keen to set up or who have already set up their own internal data science communities. It’s an excellent way for companies to promote data science culture and methodologies, upskill employees and encourage collaboration across different teams, sites or departments.

If you or your company is keen to find out more about how Mango can help your data science journey, get in touch with us or take a look through more information here.

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RStudio have recently announced ‘RStudio Connect QuickStart’ which is a VM containing a full suite of RStudio’s pro tools, available to be trialled for a 45 day period. RStudio Connect Quickstart allows R users and people exploring the idea of using R in production, a quick and easy way to set-up a full, production-like environment that contains all of RStudio’s enterprise-grade products.

In essence, RStudio Connect quickstart is a virtual machine appliance that when used with your favourite virtualisation software (Virtualbox,VMWare etc) will create a ready to use environment containing the following tools;

  • RStudio Server Pro
  • RStudio Connect
  • RStudio Package Manager
  • Webmail (for checking emails from RStudio Connect)

This means tools like RStudio Connect, which is professional software that runs on Linux servers behind a company firewall, can now be set-up locally on a users machine within a matter of minutes. This means the user is able to get a feel for the products and experiment with their functionality. This includes things like: hosting Shiny applications, scheduling and distributing R Markdown documents, and exposing R functions as APIs.

Using RStudio Connect Quickstart

Using RStudio Connect Quickstart is relatively straightforward. Once you have downloaded the Quickstart virtual appliance from here, you then need to import this into VirtualBox or other similar virtualisation product. No further configuration is needed from this point and the virtual machine should start straight up. (Running the Virtual Machine in headless mode is recommended which will start up the environment, without displaying an ugly terminal screen on your desktop.)

Once the Virtual Machine has fully booted, navigating over to http://localhost:5000 on your desktop’s web browser will present you with a welcome page with links to RStudio Connect, RStudio Server Pro, Package Manager and the webmail client.

Creating and Deploying a Shiny app

Creating and deploying a shiny app in QuickStart is really efficient and easy. In this case, I have created some basic charts that I would like to deploy on to RStudio connect. To do this I just press the publish button, specify the URL of RStudio Connect, which in this case is http://localhost:5000/rsconnect (ensure you specify http and not https!).

The Shiny app is now deployed to RStudio Connect and is automatically opened for me to view in a separate browser window.

Old Faithful Geyser Data

Here you can see that I have deployed the default ‘Old Faithful Geyser Data’ app onto RStudio Connect directly from the RStudio Server IDE. Now that my Shiny app has been deployed into RStudio Connect, I can set who can and can’t view it as well as customise performance related settings in the ‘Runtime’ menu to the right.

Publishing an R Markdown Document

In the same way we can deploy Shiny apps, we can also publish R markdown documents. The great thing about RStudio Connect is that we can set a schedule in which we would like the knitted R markdown document to get emailed out on, as well as access it directly from the Connect UI.

In my case, I would like mine to be knitted and emailed to my colleagues every Friday evening. To do this I just need to go into the ‘Schedule’ menu, pick a date and a time that I would like this to go out, and then save the changes. Now my knitted R markdown document will get sent out to the recipients that I specified, every Friday evening.

Final Notes

The wide range of uses and functions the RStudio Connect Quickstart offering provides is perfect for testing, trialling, or just getting to know the superb range of products that RStudio offers. I would encourage everyone to give it a go and have a play around with some of the features it provides, In particular, RStudio Connect and the newest RStudio product family member, RStudio Package Manager. RStudio Package Manager helps you, your team, department or company centralize and organise your R packages which is ideal for environments where connectivity to resources outside of your company network is restricted or blocked.

For more details on using RStudio Connect QuickStart see https://www.rstudio.com/products/quickstart/.

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My first LondonR took me back to my days at University as UCL hosted us for the evening.

Our first speaker of the night was Mike Smith from Pfizer. Mike had joined us to give a version of his talk that he delivered at this years rstudio::conf – ‘lazy and easily distracted report writing in R’. While there was a strong focus on his (wonderful) tidyverse themed t-shirt and his messy kitchen drawer, Mike had some home truths for us – we all get distracted very easily! This is why it’s so important to produce rmarkdown reports that help you to remember exactly what you were doing, not only for future you, or different people – but for presently distracted you!

He also emphasised how vital knowing your audience is, then showed us how easy it is to adapt an rmarkdown report for various audiences by parametrising your rmarkdown reports. I won’t go in to any detail here but definitely something worth looking in to if your work (or play) involves producing rmarkdown docs for multiple audiences.

After Mike’s talk, Laurens Geffert from Nielsen Marketing Cloud showed us how to build a supercomputer using the cloudyr project and AWS. Laurens definitely got the message across that R can be made into a very powerful tool very easily. Something we can all relate to is how Laurens code has progressed over the years; from base R, to purrr, then on to furrr! Dropping package names like it was going out of fashion Laurens introduced us to a suite of packages for parallel computing on AWS; aws.ec2, future, remoter and the aforementioned furrr the stars of the show. He ended his talk with a call to action, the cloudyr project are looking for people to help with maintenance of their AWS packages (if this sounds like something that interests you then check out github.com/cloudyr ).

Our last speaker was Mango’s very own Hannah Frick – providing the low down on all the news from this year’s rstudio::conf. This year’s conference was held in Austin and featured titans from the R community such as Joe Cheng and Hadley Wickham. Hannah didn’t have time to tell us about all the brilliant talks in a half an hour presentation – so I certainly won’t try and do it here. What I can offer is a link to all of the materials from the conference here, and all of the sessions were recorded and are freely available here for your viewing pleasure.

The night ended with a shameless plug for our annual EARL London conference in September (abstract submissions close on the 31st of March!). If you’re looking for a reason to attend, or more likely convince your boss that you should attend, then look no further than this blog post.

All the information from this event and past LondonR’s can be found at londonr.org. We hope to see you all again at the next one on the 15th of May – again at UCL. We’re always looking for speakers so please get in touch if you’ve got anything to talk about!

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At Mango, we talk a lot about going on a ‘data-driven journey’ with your business. We’re passionate about data and getting the best use out of it. But for now, instead of looking at business journeys, I wanted to talk to the Mango team and find out how they started on their own ‘data journey’ – what attracted them to a career in data science and what they enjoy about their day-to-day work. (It’s not just typing in random numbers?! What?!)

We are hugely fortunate to have a wonderful team of data scientists who are always generous in sharing their skills or don’t mind teaching the Marketing and Events Coordinator (me) R for uber beginners. So let’s see what they have to say on becoming a Mango…

Jack Talboys

Jack joined us last year as a year-long placement student 

“I actually had no idea what Data Science was until I discovered Mango about a year and a half ago. I was at the university career fair – not really impressed by the prospect of working in finance or as a statistician for a large company. I stumbled across Liz Matthews and Owen Jones who were there representing Mango, drawn in by the title “Data Science” we started talking. Data Science seemed to tick all of my boxes, being able to use my knowledge of statistics and probability while doing lots of coding in R.

I’m now 6 months in at Mango and it couldn’t be going better. I’ve greatly improved my proficiency in R, alongside learning new skills like Git, SQL and Python. I’ve been given a great deal of responsibility, assisting in delivering training to a client and attending the EARL 2018 conference making up some of my highlights. There have also been opportunities for me to be client-facing, giving me a deeper understanding of what it takes to be a Data Science Consultant.

Working at Mango hasn’t just developed my technical skills however, without really noticing I’ve found that I have become a better communicator. Whether organising tasks with the other members of the ValidR team or talking to clients I have discovered a new sense of confidence and trust in myself. Even as a relative newbie I can see that Data Science as an industry is growing massively – and I’m excited to be part of this growth and make the most of the exciting opportunities it presents with Mango.”

Beth Ashlee, Data Scientist

“I got into data science after applying for a summer internship at Mango. I didn’t really know much about the data science community previously, but spent the next few weeks learning more technical and practical skills than I had in 3 years at university.

I’ve been working as a Data Science Consultant for nearly 3 years and due to the wide variety of projects I’ve never had a dull moment. I have had amazing opportunities to travel worldwide teaching training courses and interacting with customers from all industries. The variety is my favourite part of the job, you could be building a Shiny application to help a pharmaceutical company visualise their assay data one week and the next teaching a training course at the head offices of large companies such as Screwfix.”

Owen Jones, Data Scientist

“To be honest, it rarely feels like work… since we’re a consultancy, there’s always a wide variety of projects on the go, and you can get yourself involved in the areas you find most interesting! Plus, you have the opportunity to visit new places, and you’re always meeting and working with new people – which means new conversations, new ideas and new understanding. I love it.”

Nick Howlett, Data Scientist

Nick is currently working on a client project in Italy.

“During my time creating simulations in academic contexts I found myself more motivated to meet my supervisor’s requirements than pursuing niche research topics. Towards the end of my studies, I discovered data science and realised that the client-consultant relationship was a situation very similar to this.

Working at Mango has allowed me to develop personal relationships with clients across many sectors – and get to know their motivations and individual data requirements. Mango has also given me the opportunity to travel on both short term training projects and more long term projects abroad.”

Karina Marks, Data Scientist

If you’d like to join the Mango team, take a look at the positions we have currently.