Company

At Rotageek, we believe that effective optimised scheduling is one of the most interesting data science challenges and in a world increasingly reliant on flexible working, one of the most important. Our approach at Rotageek is to balance organisation and individual needs to create work schedules that deliver measurable value for our customers and their clients, whilst also empowering staff to better manage their work-life balance. Seeing the real-life impact of our work in solving complex scheduling problems is what drives us.

Having established a market, built a great team, and secured multiple rounds of funding, Rotageek is now seeking to take its data science team to the next level by hiring a senior data science leader.

Role

You will help transform existing approaches already in use by hundreds of thousands of workers inside household names like Pret, RAC, Pets at Home and Sephora to make them faster, more flexible, scalable, and applicable to a broader client base and problem set. Bring your best thinking to solving complex optimisation problems within a large solution space, as well as your passion for leading smart teams of data scientists, mathematicians, and engineers toward a real-world application that saves time improves lives and takes the pain out of workforce management. If you think scheduling should be better, you might be a Rotageek.

Requirements

Essential:

• Smart, results-focused, and inquisitive

• Graduate degree in relevant field or equivalent experience

• Proficient in C/C++/Python

• Experienced with distributed cloud computing

• Up-to-date with the latest approaches to large-solution-space optimisation problems

• Able to communicate well, hold a clear vision, and support your teammates

• Comfortable in an agile development environment

• Able to contribute to a data science strategy

• A strong self-starter able to work remotely and keep everyone focused on the goal

• Bringing in ideas for new approaches and tools, and being able to justify their

  relevance

• Passionate about getting it right at every stage of the data science pipeline, from initial gathering and grooming of data to performance testing to observability of solutions in deployment

Desirable

• Experienced with MLOps in a cloud environment

• Experienced with both AWS and Azure environments

• Experience in solving optimisation problems

• Experience with Machine Learning

• Experienced with a broad range of machine learning approaches and tools

• Track record of recruiting and managing top-calibre teams