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Thrive is set up by Funding London, a venture capital company bridging the finance gap for early stage businesses based in London. With over a decade’s experience in supporting the startups of London through a variety of funding vehicles, Funding London sensed a need to illuminate the ever-evolving scenario of London’s early stage businesses.

Thrive features interviews with and opinion from budding entrepreneurs, investors and industry experts. A mix of contributors from all areas of the industry is desired in order to spark genuine discussion about ongoing critical issues. While it showcases the effectiveness of successful ventures, it also encourages sharing lessons learned from missteps and unsuccessful projects.

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Demystifying Data Science


Kim has a background in Astronomy with a PhD from Copenhagen University, and held the title “Hubble Astronomer” in her last science job. She then completed an MBA from Cranfield University before co-founding Pivigo. She has been named a Rising Star among the Top 100 Influencers of Big Data in the UK.

25 January 2017

Tell us the Pivigo story.

Pivigo was born when I met my co-founder Jason during our MBA programme. My background is in science, as a PhD in Astrophysics, and Jason founded a couple of recruitment businesses before his MBA. Together, we became very passionate about connecting industry with the fantastic, talented pool of analytical MSc’s and PhD’s in our Universities, while at the same time supporting their career transitions into the industry.

We started the business almost four years ago, but it has evolved significantly along the way as we refined our business model and found new ways to support the data science industry. Raising our first round of funding last year put us on a new path, building our data science marketplace. This is the part of our business that we are very excited about right now!

What is the S2DS programme?

S2DS is Europe’s largest data science training programme. It is a five week, so-called ‘bootcamp’, that mixes PhD’s and MSc’s with companies, with the participants working on real, commercial data science projects proposed and mentored by the companies. At the end, the outcomes often get implemented into the products and services of the partner companies, and the participants often land a job offer. We have run this programme six times t0 date; with 320 participants working on over 80 projects with 60 clients including corporate giants like KPMG, Barclays, M&S, British Gas and Royal Mail.

What are the key objectives of the model that you have developed?

We started S2DS as a way for industry to get together with analytical PhD’s so that they could experience directly just how smart and highly skilled they are. In my experience, companies want to be more data-driven and they want to do data science, but they don’t know how to get started or how to hire data scientists. S2DS took away both those pains by letting the companies run short-term projects with the participants, as well as potentially hire the team members at the end of the programme.

The latest service we have developed and which is officially launching 24 January is the data science marketplace. Having completed over 80 short-term data science projects with companies and data scientists from our community, we saw endless amounts of potential in connecting businesses with this community anywhere, anytime. The marketplace allows companies looking for freelance support on data science projects to connect with our community of thousands of data scientists across the globe, at various experience levels.

How has been the response from the industry?

Brilliant, I would say. Every year I sense an increase in interest in data science projects and machine-learning applications in the companies I speak with, and I also believe that the understanding of what it takes to run a successful data innovation programme is improving. In the first years, most conversations were around whether to do data projects at all or not. Today, the conversation tends to be more around the ‘how’ instead. That is encouraging. I also feel that many companies are keen to limit their risk on the investment, by taking on temporary or freelance staff with proven skills and experience to complete proof-of-concepts and build prototypes, rather than hiring and committing to long-term salary budgets.

What are the pain points of operating in a niche area like data science?

One of the concerns that are always at the back of our mind is of course that around data security and privacy. Our clients’ data are extremely valuable to them and cannot be compromised. Similarly, many organisations have very strict data sharing and handling policies that we need to respect. Whereas these considerations are all beyond questioning, it does sometimes mean that there are limitations to the projects. At Pivigo we are working on further solutions to these data sharing challenges.

A second area would be around the buzz. There is so much hype and buzz around data science, Big Data and AI, and sometimes it can be difficult for inexperienced managers to cut through the clutter. At the core of innovations in data is data mining and machine-learning, call it what you may. It requires special skills in programming, statistics and data handling but is not rocket science. And it can transform a business from a failing or mediocre business to an industry leader, within a very short period of time, if done right. Quite simple really.

How would you describe your funding experience in London?

Educational, frustrating, exhilarating. London is without a doubt the best place in Europe to start a tech business; not the least because of the access to early stage capital. There is certainly a lot of money floating around for those that have a good idea, a good team, and a good pitch. This is where the educational experience came in for me. Initially, we had a good idea and a fantastic team, but getting the pitch right was hard work and took a long time. This lead to the frustration, specifically with the long timeline between starting to fundraise and closing. Mostly it was frustrating because I knew it would work, I knew it would be a great business, and I just wanted to get on with it. When the deal was finally done, and in the six or so month since it has been exhilarating though. The support and acknowledgment we received from our investors was a huge boost, and growing the team from four to twelve over the Autumn has been great fun. The Pivigo team is awesome.

What are the three factors that you think influenced investments in Pivigo?

There are a couple of trends coming together in a business such as ours. Number one is the increased interest in data science, machine-learning and AI. There is a lot of buzz and hype, but also a lot of truth in that these disciplines can and will change our lives for the better. At the moment, many investors are keen to invest in data related start-ups, which helped us.

Second, there is a trend towards more freelance and outsourced work. Companies such as Upwork, Uber and Freelancer are re-defining what a career means in the so-called “Gig Economy”. Our data science marketplace is offering a freelancing opportunity for highly educated individuals who may not be so keen on full-time jobs with the same employer long-term.

The third element that I think was very important to investors was to see that we were not only already revenue-generating, but actually profitable. That de-risked the opportunity for them, and made us a credible player in this exciting and growing market. We didn’t just have a great idea and a great team; we also showed that we can execute on a plan and deliver a good cash flow.

How do you plan to use the new investments that you have secured?

The funds we raised last summer have already been put to good use growing our team and scaling our business. We have started a new tech team that have worked very hard to get the data science marketplace ready for launch this January, and the sales and marketing team grew in parallel. So far we are well on track towards the targets we set ourselves for growing our business using the funds, and the increased team has been very exciting to work with.

What are your growth plans for Pivigo?

This Spring we are working extremely hard to grow the data science marketplace. This is a global opportunity in a fast growing market and so all our efforts are geared towards bringing out the message of the benefits of data science and AI for businesses, and of course to get more analytically minded individuals excited about data science careers. From there, it is really only a matter of scaling; in size, in turnover and geographically. Data science will revolutionise the way we live, work and play, and Pivigo will be there to support that revolution all the way.