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Data Scientist, Product Analytics 26 views

They’re looking for a Product Data Scientist excited to help build the bank of the future. You’ll have the opportunity to supercharge their user engagement in 2021 and help them to build a bank that customers truly love.

At Monzo, they’re building a bank that is fair, transparent, and a delight to use. They’re growing extremely fast and have over four and a half million customers in the UK, with over 100,000 new people joining every month. They’ve built a product that people love and more than 80% of their growth comes from word of mouth and referrals.

Their Product Analytics team’s mission is to

Enable Monzo to Make Better Decisions, Faster

They have a strong culture of data-driven decision making across the whole company. And they’re great believers in powerful, real-time analytics and empowerment of the wider business. All their 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 headspace to focus on more impactful business questions and analyses.

They work in cross-functional squads where every data scientist is a member of a central data discipline and fully embedded into 1 product squad alongside engineers, designers, marketers, product managers, etc.

As part of your role, you’ll:

    • Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how their users interact with their products and how those insights can inform their product strategy
    • Guide and enable product teams to measure things that matter; initiate or help run A/B experiments to keep improving everything they do
    • Drive together with the finance team a unified company-wide understanding of the lifetime value of their users and how different product features are impacting user profitability
    • Liaise with engineers to keep making sure they collect the right data to produce relevant business insights

What’s special about data at Monzo?

Autonomy. They 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 their 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 their data infrastructure lives on the Google Cloud Platform, so you don’t need to spend your time configuring or managing clusters, databases, etc. If you want to train a Machine Learning model faster, just spin up a compute engine instance and submit a job from your local machine, no DevOps skills required.

Automation. They aim to automate as much as they 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 they encourage self-serve access to their data through Looker.

You should apply if:

    • What they’re doing here at Monzo excites you!
    • You’re impact driven and eager to have a real positive impact on the company, product, users, and very importantly your colleagues as well
    • You’re commercially minded and can put numbers into a business perspective
    • You’re as comfortable getting hands-on as taking a step back and thinking strategically
    • You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
    • You’re a team player whom your colleagues can rely on
    • You have a solid grounding in SQL and preferably Python
    • You have experience in conducting large scale A/B experiments

Nice to have:

    • You have multiple years of experience in product or growth analytics, preferably in a fast-moving tech company
    • Experience with complex statistical approaches (causal inference, machine learning, Bayesian statistics)

Logistics

They can help you relocate to London & they can sponsor visas.

They offer share options and competitive salaries based on skills and experience.

Their interview process is normally a phone interview, a take-home task and call to discuss it, and 2-3 hours of onsite interviews. They promise not to ask you any brain teasers or trick questions.

Diversity and inclusion is a priority for them – if they want to solve problems for people around the world, their team has to represent their customers. So they need to attract the best talent and create an environment that supports and includes them. You can read more about diversity and inclusion on their blog.

If you prefer to work part-time, from home, or as a job-share, they’ll make this happen whenever they can – whether this is to help you meet other commitments or strike a great work-life balance.

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