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So what does a typical data science consultant look like I hear you say? Well, we have assessed the skills and competencies of one of own data science consultants using Data Science Radar.

Mango’s Data Science Radar maps the many and varied competencies in the field of data science against six core data science traits. These traits quantify relative strengths and areas for improvement  for individual s as well as at a team level  – ultimately enabling users and team leads to make decisions based on evidence rather than intuition.

Here’s what we discovered when we analysed one of our consultant’s persobal radars:

Name: Karina Marks

Job title: Data Science Consultant

Qualification(s): MMath

Number years in current role: 3 years

Karina’s expertise in her role demonstrates strong programming skills in both R and python and shiny app development. As one of Mango’s lead trainers, she supports building team capability and demonstrates superb communication skills, with the ability to explain complex concepts to both technical and non-technical audiences. Much of Karina’s work is centred around her knowledge and expertise in this field and generally making teams more efficient through automation.

 

 

Karina’s top 3 traits:

  • Programmer
  • Communicator
  • Data Wrangler

 

Karina, when you first got your results back from the radar, did any of the results surprise you?

“In general no, I do think that my radar is a true reflection of my current skillset. I expected to be a high communicator and programmer, which I am, but I expected slightly higher on the modeller as that was part of my degree. However, the projects that I have worked on at Mango over the past few years have not been focussed on modelling and so I have not been utilising those skills recently, which is reflected in my radar. This does go to show that modelling is only a small proportion of what we do as Data Science Consultants and not every Data Scientist needs to come from a mathematical/statistical background”.

 

What impact has the radar had on your recent work?

“I was involved in a long-term project that was to develop the capability and training support for ~ 3k employees who were moving to a new Cloudera data platform from their current complex network of different systems. My role was to provide the technical support for those moving onto the platform, whether they were using excel, SQL, R, Python, or Spark. My communicator and programmer skills here were key for this and meant I was an ideal fit for this project. Not only could I effectively communicate to different teams in understanding their needs for training and support for this new platform, but I also had the programming skills to be able to write materials and provide individual technical support to those who needed it”.

Which parts of your radar would you like to improve the most and why?

“I would like to improve my communicator and visualiser skills more. I think they are key skills in many of the projects that I wish to work in, and as I enjoy working closely with clients – having those strong communication skills are essential”.

Are you looking to build the ultimate data science team and want to know more? Check out our Building a Winning Data Science Team page.

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You might think it a bit trivial to be writing about ‘respect your cat day‘ in the current climate, and you would be right! But just for one short blog post, let us enjoy some trivial cat content.

Real-life Mango cats

I would bet good money almost every cat owner would argue that respecting your cat is not a trivial notion. More often than not, a household with a cat is at the mercy of their said feline’s whims and moods. I remember being frozen with fear when Jess, my best friend’s quite frankly ‘evil’ cat, would sit on my lap – only to swipe a razor-sharp paw at me seconds later if I dared to breathe.

Evil Jess and evil Jess on my lap – smiling but crying inside

At Mango Solutions, our history with cats goes right back to the birth of the company. When owners Matt and Rich sat down to work out their new company’s name, they toyed with questionable ideas such as ‘Stats Entertainment‘, but thankfully, Matt’s cat ‘Mango’ kept pouncing on their desks and generally getting in the way. With pressure mounting for them to quickly name the new company, only ‘Mango’ kept coming to mind, and so ‘Mango Solutions’ was born!

The original Mango

If you have ever seen Mango Solutions exhibiting, or if you have attended our EARL Conference, you will come across a table of ‘Mango the Cat’ soft toys for you to take home. We are certainly still a company of cat-lovers (well most of us are…) to this day and I will personally take advantage of any opportunity to compile pictures of cats!

 

More cats of Mango

Author: Laura Swales, Marketing and Events Coordinator

 

Rich Pugh makes DataIQ Top 100 list
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Earlier today, DataIQ unveiled its list of the 100 most influential people in data-driven business, the DataIQ 100, and I’m delighted to report that I was included on that list. It was humbling to be counted among talented individuals, such as Harry Powell, Orlando Machado and Tom Smith, all of whom are blazing the trail in using data to make a real difference in the way they drive their businesses.  The competition was stiff, with a record breaking 1,000+ entries for the coveted 100 places, so we must have done something right along the way!

But as well as being a moment of personal pride, it was actually refreshing to receive good news this week after what feels like a growing sense of doom in the world with the current Covid-19 outbreak.  A beacon of light in dark times, if you like. It’s an interesting time for data scientists: the world is witnessing the bravery of medical staff on the frontline dealing with those affected by the illness, but #flattenthecurve is trending and tales of retail boom or bust (depending on what sector you’re in) are just two examples of data-driven stories that highlight how our profession is trying to make some sense out of this unfathomable situation.

Initiatives such as the DataIQ 100 help showcase the value and positive impact that data can have on business and situational outcomes.  We at Mango are firm believers in the power of data and (advanced) analytics to drive better decisions, not just in the world of business, but to help the most vulnerable in our society and help combat some of the biggest threats facing our future.

Some time ago, the DataIQ 100 committee asked me, and other members of the 2020 DataIQ 100 list, for our views on the industry’s future, and one of the key themes to emerge from this was skills.  The feedback was unanimous, that demand will continue to outstrip supply.

At the end of 2019, Mango, alongside Women in Data, conducted its own research into this topic and discovered that over half of data scientists planned on moving roles within the next year.  A lack of support, funding and time available for upskilling were all cited as challenges within the UK data science community – all indications that vital steps need to be taken to assess skills gaps and plan to unite individuals to create effective, skilled teams that can rise to the growing data challenge for businesses.

I hope that the important work data scientists are doing in the background of this current crisis – from work in the pharmaceutical sector to expedite the release of a vaccine, to work in the retail sector to ensure firms can weather this storm or that food supply chains run smoothly – can shine a light on the difference that data can make and encourage others to join the profession in the future.

In the meantime, I am proud to be included among such industry luminaries and hope that, together, we will be able to inspire others to join our crusade.

Here’s my #DataIQ100 profile 

 

building project teams
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Project managers guide to playing to a team’s capability with Data Science Radar

Data science consulting is a rapidly evolving beast that is often difficult to tame. The many moving parts require a broad set of capabilities that, in many cases, simply don’t exist in any single person. Engaging our customers in what is a relatively new discipline, and one which is rife with exaggeration, misconceptions and misaligned expectation requires a team effort. To be successful, finding the right fit of team is a critical component of working productively at both technical and strategic level. For us, Data Science Radar (DSR) enables an efficient and effective route to building project teams aligned to both the culture and needs of any client. And it can do the same for you.

Building the winning formula for your team

Beyond the shape and relative strengths that one can evidence by looking at the output of DSR, I’d suggest it’s the inputs that are most important. The language of advanced analytics can be ambiguous at best, so having a tool that makes clear how analytics can be categorised around central themes provides a foundation that has brought our organisation together.

Mango isn’t unique in the way it might conduct its’ business, but I’ve yet to see another consultancy that has a common language set that enables everyone – practitioners, managers, leaders and support staff – to understand relative skills and capabilities in such a diverse and complex environment.

Why is this important?

Knowing the Radar’s of your team gives a greater understanding of the skills, capabilities of the whole team or common language to manage resourcing. My belief and observations are that having a common language enables our whole organisation to understand and talk about what we do. This brings us together, helps us build a commonality of purpose, and means that what we present to the outside world is more powerful. Additionally, the route to our messaging is more efficient and on point. Having an organisation that can sing from the same hymn sheet (my Welsh roots coming through here!!) sounds like an obvious requirement to building a data-led culture.

Strategically and culturally DSR has provided a platform for us to get stronger. But its more than a strategic platform. Operationally, DSR is used everyday to identify who in our team may have the best technical skills to deliver projects and bring value to our clients (Fig 1). Not just individually, but as a project team. Getting the right mix of skills, all executing aligned to respective strengths, means we can be confident to deliver on time and to the exacting standards we set ourselves. Being the right cultural and strategic fit only takes us so far – backing this up with the right technical mix ensures success across the full project lifecycle.

Develop and retain key skills

As a growing company in a fast-moving industry its critical to continually attract, develop and retain key skills and capabilities. Many of our staff have a strong desire to continually grow themselves and are keen to engage in professional development wherever opportunity presents. In some cases, this happens as a natural consequence of engaging in a wide variety of project work. But in others, it happens due to development planning aligned with our career framework. Before DSR, this meant looking at generic descriptions of technical capabilities – eg using, teaching, mentoring, coaching in R – which whilst valuable didn’t offer a level of specificity many of our team were after. Post DSR, we’re able to explicitly align development needs with DSR traits and allow our team to grow capabilities in the areas that are of most interest to them. We can also guide and shape this outcome based on business need, meaning we have a significantly more engaged workforce with a set of skills that the business needs. It’s a win-win for everyone, including our clients.

Software as a service

Data Science Radar is a piece of software, powering analytic capability. It isn’t a panacea that provides users with a utopian state of analytic health, nor is it the silver bullet that ensures everyone in your organisation understands the language of analytics. But it can be the differentiator that helps secure competitive advantage.

Gartner indicates that 80% of analytic projects fail. Reasons vary from lack of executive buy-in, misaligned expectations, disconnect between technical teams and users, and ill-defined business problems. DSR doesn’t eradicate these problems, but it does provide a platform through which many of these issues can be surfaced, discussed, understood and acted upon. Once better understood, it can then be used to ensure the right people are tasked with the right actions to execute effectively. DSR removes square pegs commonly put in round holes. It can bring an organisation together; help empower growth and provide clarity in terms of existing capabilities. Once you know these things, building project teams for the future becomes a natural next step, and keeps you always looking at where the gaps are, and how to close them.

We never built DSR to close strategic or cultural gaps, but that’s what it has done. And its enabled a more empowered and more engaged technical workforce too.

Pete Scott is Client Services Director here at Mango. For more infomation about a demo of Data Science Radar please click here.

R language
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Happy 20th BiRthday, R!

If you’re kind enough to follow my blogposts, watch my YouTube videos or attend any of my presentations, you’ll be very familiar with my belief that data-driven success in any organisation is two-thirds due to people and processes, and only a third due to technology. Am I being unduly hard on the technology?

A poor worker, it is said, always blames their tools, and if that’s accurate, then we must surely also credit the tools when the workers get it right. Today seems like an appropriate day to shine the spotlight on one of those tools: the R language, which this year celebrates its 20th anniversary!

I guess any milestone anniversary forces you to take a moment to reflect on a journey that has taken place, but this anniversary is particularly close to our hearts as it’s the language that Mango was really built upon back in 2002.   With less than 10 employees three years later, we offered our first R consultancy project and we did – and still do – play an active role in the R community, hosting meetup groups and events around the world to nurture talent and promote the latest innovations.  Indeed, Mango was a founding member of The R Consortium, a group which aims to offer support to key organisations and groups developing, maintaining, distributing and using R software.

One of the events we organise is the annual EARL Conference in London, an event dedicated to the commercial use of the R language.  Every year it’s awe-inspiring to see the breadth and calibre of presentations go up and up, along with the attendee numbers.  I believe this year we are expecting 400+ attendees and 64 presentations from all sectors, as some of the world’s leading practitioners share their projects, ideas and solutions with the audience. My favourite part of this conference is learning how data scientists are using R to make other people’s lives better, whether that be in medical research, social care, improving transportation or even aiding the peace process in Colombia.  Heady stuff.

Originally conceived as an idea in 1992 by Ross Ihaka and Robert Gentleman in Auckland, New Zealand, its name, R, comes from the first names of the authors, as well as being a nod towards S, the language that preceded R.

It’s easy to see how the language has grown in popularity to supporting over 2 million users today:

  • It’s free to use; a compelling proposition when you consider costly alternative proprietary software licenses
  • Advanced Analytics: Because of R’s architecture and licensing the very latest algorithms from research are readily available. This makes R an ever-evolving language which encapsulates the most modern statistical techniques and practices.
  • High-quality reporting: The ease at which high-quality graphics and interactive web applications can be created and written to a multitude of devices has seen R set the standard for graphical analytics. Tools such as R Markdown allow users to weave together narrative text and code to produce elegantly formatted reports.
  • Easy to integrate and extend: Many business intelligence systems and statistical reporting platforms now offer R connectivity as part of their extended offering; it links easily to various data sources and other programming languages enabling users to make use of additional algorithms and power up their statistical capabilities.

But perhaps one of the key drivers in the success of the R Language is that it came along at exactly the right time.  In the last 20 years organisations have been looking to use data and advanced analytics to generate value and change, and R’s openness together with its incredible community has really been around at the right time to enable that.  It has enabled the data science movement to gather momentum, breaking new ground at the same time by driving things like modern data visualisation thinking and integrating with evolving big data technology.

Perhaps R hasn’t yet come of age, but as I look back over the last twenty years, I feel proud to have been at least a small part of its growth.  I can’t wait to hear what more has been achieved with the language at this year’s EARL event and, even as a proud Welshman, if it steers England to win the Six Nations tournament, I’ll certainly give the tool the credit it deserves!

Happy 20th Birthday, R!

 

Author: Rich Pugh, Chief Data Scientist