Python Job: Data Scientist Manager

We're looking for Data Science Managers to help our product teams build the bank of the future. You'll have the opportunity to lead a team of Data Scientists across our Operations collective.

As we continue to scale, we're looking for an Operations Data Science Manager to lead our WFM workforce management team within operations.

As a Data science manager, you'll be working in an ever changing environment where we are building and iterating on our workforce processes and systems to ensure we keep delighting our customers. Your team will focus on how to optimise costs by improving our forecast and planning capabilities and supporting decisions on how to improve our service and systems.

We're still growing, and this is the right time to review our tools, processes and operational footprint. You'll help us build and improve these for now and for our future roadmap. We're looking for a hands-on, data driven operational leader who can bring fresh thinking and new ways to inspire the team to deliver service excellence.

You'll work closely with product managers, engineers, designers and researchers in an agile product environment. You'll champion the use of data, bring ideas to life through rigorous experimentation and A/B testing. You'll help us get the most out of volumes of cloud native data platform, spotting opportunities to make each area of our product work even better for our users. You'll help your team grow, hiring new team members, supporting their personal development. Your team will drive product innovation and you'll get to see the impact of all your work in the product changes we make.

We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. All our data lives in one place and is super easy to use. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.

We work in cross-functional squads where every data scientist is a member of a central data discipline and fully embedded into a product squad alongside engineers, product managers, machine learning engineers etc.

As part of your role, you'll:

• Be a key leader in building a discipline of exceptional data scientists working on making Monzo world class at tackling operations problems
• Assure that our forecasts are accurate and flexible
• Help hire, develop and retain talented Data Scientists
• Generate insights that can change the direction of product development
• Establish yourself as a trusted partner to the product leadership teams with the capacity for getting things done, be it either hands-on or by leading others
• Bring data leadership and rigour to our approach to product development in the operations function and build a strategic understanding of the business while structuring complex projects to bring them to life
• Liaise with engineers to keep making sure we collect the right data to produce relevant business insights

What's special about data at Monzo?

Autonomy. We believe that people reach their full potential when you can remove all the operational obstacles out of their way and let them run with their ideas. This comes together with a strong sense of ownership for your projects. At Monzo, you will get full access to our data and analytics infrastructure. When you discover something interesting, there is nothing stopping you from exploring and implementing your coolest ideas.

Cutting-edge managed infrastructure. All our data infrastructure lives on the Google Cloud Platform, so you don't need to spend your time configuring or managing clusters, databases, etc. All of our infrastructure is designed so that we can have really high data quality, and spend most of our time using that data to support business decisions.

Automation. We aim to automate as much as we can, so that every person in the team can focus on the things that humans do best. As with all data science work, there's some analysis and reporting, and as much as possible we encourage self-serve access to our data through Looker.

You should apply if:

• What we're doing here at Monzo excites you!
• You have multiple years of experience as a Data Science Manager, working as a Lead data scientist or Data Scientist
• Experience in forecasting or operational research is a plus
• You know what it takes to manage top tier Data Science talent
• You're excited by the opportunity to work autonomously to impact the future of a fast growing, ever evolving business
• You consider yourself an empathetic leader and have experience managing data scientists and you really enjoy that part of the job
• You have experience working together and collaborating with senior business stakeholders and product teams
• You're familiar with using a variety of Data Science tools (from business intelligence, experimentation and causal inference through to machine learning), and coding languages (Python and SQL). You know when to pick the right tool, and can help others do the same

Logistics

• We can help you relocate to London & we can sponsor visas.
• This role can be based in our London office or remotely within the UK
• We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
• Diversity and inclusion is a priority for us – if we want to solve problems for people around the world, our team has to represent our customers. So we need to attract the best talent and create an environment that supports and includes them. You can read more about diversity and inclusion on our blog.
• If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
• The application process consists of a 30 min phone call with a recruiter, an initial call with someone from the team, followed by a practical exercise and 2-3 video interviews. We promise not to ask you any brain teasers or trick questions.

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