Lead Data Scientist – Operations Research – £100,000/yr – £120,000/yr

Location Icon 100% Remote/ Hybrid/ London
Permanent

Lead Data Scientist – Operations Research – £100,000/yr – £120,000/yr


Unless this is the first job advert you’ve read, you’ll have noticed that a lot of companies use the job title ‘Lead Data Scientist’ to mean “one of our senior data scientists”. Read on and the job usually turns out to be overwhelmingly doing data science, day in, day out.

This job couldn’t be more different.

Here, you’ll play a true leadership role – it’s a genuine opportunity to lead a data science team, transform the company’s product and help to turn a successful start-up into a scale-up business.

 

Where you come in

You’ll join a business that’s established a market for its optimised work scheduling product – they help some of the world’s leading organisations to create work schedules that deliver measurable commercial value and give staff a better, fairer work-life balance.

They’ve secured multiple rounds of funding and built a great team. Now they’re ready to take their data science team to the next level – and that’s where you come in.

From a data science perspective, your role is to help make the product faster, more flexible, more scalable and applicable to a broader client base and problem set. Working at every stage of the data science pipeline – from gathering to performance testing – alongside some smart colleagues you’ll be solving complex, engaging optimisation problems within a large solution space. It’s a chance to employ your best thinking and delve deep into things like data optimisation, machine learning algorithms, AI, EPUs and TPUs.

Then there’s the leadership aspect of the role – and this is where you can make a huge difference.

  • You’ll be the subject matter expert, working closely with the CEO, CTO and colleagues in Product to shape the data science strategy and influence the long-term shape of the product. If you enjoy injecting ideas and suggesting fresh approaches, you’ll love the role.
  • You’ll hire, and develop a small, smart team of data scientists, mathematicians and engineers – a great chance to develop your team leadership skills and to communicate a vision to others.
  • You’ll help transform a positive real-world application that helps employers including NHS Trusts and high street stores to take the pain out of workforce management, save time and improve their people’s lives. You’re working for the greater good.

 

About the business

This is a successful, globally trusted, award-wining company with huge scope to really accelerate. The global workforce automation market is set to more than double to $9bn in 2022 – a strong tailwind for growth.

The leadership team really care about changing scheduling for good – and about their people. The culture is flexible, collaborative and caring. People are friendly, inquisitive, and smart. There’s a refreshing lack of egos, micromanagement or office politics. Communication from the senior team is clear and transparent – you’ll know exactly what’s expected of you and what you’re working towards.

As you’d expect, work life balance is a priority here. You’ll be empowered to work when and where it suits you – whether that’s in the London HQ, 100% remotely or a blend of the two. The company are happy to supply WeWork all-access membership plus a £250 WFH setup budget and all the hardware you need.

 

What you need

You don’t need scheduling, optimisation or labour modelling experience.

You do need plenty of experience of taking machine learning to market –

you’ve probably evolved a product or supported productized data science work.

Personally, you’ve shown you’re smart and results-focused – someone who can communicate well, support other people towards a goal, and contribute to data science strategy.

Technically, you’re comfortable using open-source tools and probably have pretty much all of these on your CV:

  • A degree in a relevant field
  • Python proficient
  • Distributed cloud computing experience
  • Conversant with the latest approaches to large-solution-space optimisation problems.
  • Exposure to an Agile environment

Nice-to-haves include MLOps (in a cloud environment); AWS/Azure; machine learning tools/approaches.

 

Find out more

To find out more about the business, the benefits and the job, click the enquire today button.

Enquire today
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