Canon_2014-07-12_541As part of our mission to become the best local partner for European startups, today we’re very proud to announce that William James has joined Creandum as our in-house data scientist.

All our work at Creandum is about giving the best service to the entrepreneurs we back. In and out of the board room we aim to be proactive on a variety of operational and strategic issues by drawing on our personal experience and network. This expresses itself in a few ways: we throw C-Bar events on important topics like product development and mobile tech trends. Our US presence is hugely important to support our companies in access to funding, partnerships and the US market. And there are certain areas that we feel we need more specific expertise and support – such as PR, recruiting and talent.

One of the biggest challenges we hear over and over again from Creandum’s portfolio companies are the difficulties of gathering and applying data in business decisions, especially as companies begin scaling. On that note we couldn’t think of a better person to have as a resource as William James, who previously worked in the team at Spotify that built the data infrastructure and frameworks that made data-driven decision making possible.

William is primarily going to support Creandum’s existing portfolio companies, but also assist in looking at new investments from a data perspective and build up our own data driven analytics.

William has a ton of experience as a full stack data guy, both in terms of developer skills and mindset but also a data scientist. To welcome him to the team, we gave him a little interview:

Creandum: To give a picture of your background, could you briefly describe your time at Spotify?
William: When I started in 2011, we were only 3 people working with data. Spotify didn’t really have a data pipeline set up yet, so when I started we had to build it up from scratch.

An example would be that when we launched in the States we built a dashboard that showed Monthly Active Users along with Registered Users. That’s how we found that some users that registered didn’t stream a song! It was the biggest launch in the history of the company, but we hadn’t started to optimize our new user experience. If you fast forward to today, the company knows the impact of any decision because we start testing it on a limited set of users, and then roll it out if the data shows it has a positive impact.

Creandum: When talking to startups, what are some of the questions you ask to understand how they use data?
Well, it’s important that they know their key metrics: How many new users are activated, how many retain and how engaged are they etc. But I’m also interested in what tools they have to leverage and understand their data. They should have infrastructure in place to easily answer any business question imaginable.

Creandum: Plenty of companies are looking for your skillset. What drew you to Creandum?
When I started at Spotify we had all this data lying around waiting to be mined. It felt like you came into work every day and found things that completely changed everything. I really liked that period because you can really make a difference. Working at Creandum enables me to not work at one startup, but multiple startups at the same time. On top of that Creandum have an amazing portfolio of companies and an equally amazing team

Creandum: Speaking of that, how can Creandum’s portfolio companies work with you in practice?
One example would be doing workshops to go through their current setup – Half day sessions to take a look at what they need to improve, what they need to track. But in some cases it might be deeper collaborations where I’d work with a company for a couple of weeks or months, set up a data pipeline, visualize the data, run A/B tests, help set up their data team, and really try to understand their use of data. I’m a programmer who happens to like statistics, so that’s the fun part for me.