I am currently working at the BBC as an interim ‘Executive’ Product Manager (which basically maps to Lead Product Manager in DDaT/GDS terms) and I have to be honest it is the most I have enjoyed my day to day work in a long time.

The ‘Datalab’ has a fascinating remit — using data science and machine learning to try and build a BBC that ‘wraps around the audience’ — providing recommendation and personalisation services that other BBC teams can build on or use as services ‘off the shelf’. It is a bit more of an internal platform play than I am really used to but has real impact on the audience facing products across the BBC. Or at least it could. It is early days and so even more interesting as you can really influence things.

Well somebody could.

Like I said — I’m an interim. This role is available and someone great should get it. This is a lovely, talented team and there are huge opportunities here. To be honest even with it being London based I’ve been very tempted to go for the role on a permanent basis! The reality is though I’m not the right person to take this team on in the longer term — I wish I was — but I’m determined to help them get someone great in.

So I’ll lay out some of the pluses:

• Great team: a mix of data scientists and engineers — very smart, very enthusiastic and open to new approaches.
• Nice environment: the office space is bright and airy. Plenty of walls. Decent wifi.
• Strong leadership: this is very much the baby of the Head of Data Science / Architecture and he really owns the vision and has the technical chops to really set direction.
• Senior buy-in: the programme has genuine support and cover from upon high.
• Interesting vision: if you are into data or machine learning — or just want to make sure you get better recommendations on iPlayer — then this is fascinating stuff.
• Salary: isn’t public but it is really good. Honest. Just ask me privately if you are interested.

It isn’t without a few minuses though:

• BBC bureaucracy: it isn’t the civil service but it is a long way from a start-up.
• Jira: god I hate Jira.

Given all of this why aren’t I going for it? Well (a) I’m not moving to London long term and while the team are flexible with location I really think this role needs to be onsite 3 or 4 days a week and more importantly (b) I think it needs a more technical, computer science-y product person (I consider myself from the humanities school of product.) Someone who gets (or can learn) machine learning and data science — at least some of the core concepts. Also probably someone who can write a little Python or something similar.

Below is a bit more about what we are looking for in the role and hopefully the proper job description will be on the BBC site soon (here it is on LinkedIn and the BBC site.) In the mean time though if you or anyone you know is interested in a chat give me a shout.

---

Role Responsibility

• Build the Datalab team — ensuring it has the skills that best enable the delivery of the BBC connected data strategy
• Develop data products and services that support the ambitions of multiple pan-BBC technical and editorial strategies
• Partner with other BBC teams teams to solve problems and identify opportunities coming from data, automation and machine learning
• Develop and manage KPIs
• Define, own and develop the data product strategy and roadmap
• Continually evolve and revolutionise the use of data and insight across platforms, audience facing products, partners and internal workflows
• As a product moves from discovery to definition, work with engineering and R&D teams to create an appropriate execution strategy

The Ideal Candidate

• Proven experience of building high performing teams with a focus on data (rather than audience facing) products
• Has a strong understanding of agile methodology and how to apply the agile mindset to all aspects of their work and that of their team
• Understanding of the different phases of product delivery and is able to demonstrate their experience of planning or running these
• Awareness of the opportunities data science and machine learning provide to reinvent business models
• Strong technical knowledge with the ability to quickly grasp data science concepts in order to truly influence product decisions
• Natural story-teller who can articulate the vision of the Connected Data strategy to a variety of audiences — including the team itself and senior stakeholders.
• Excellent team leader who inspires and encourages their teams to innovate and bring ideas to life