Job Title: Senior Data Scientist, Causal Inference
Location: Cannon Street, London
Closing Date: 30th March 2020
When you first think about Deliveroo, you probably think of getting great food to your house in less than half an hour. Awesome right? But behind the scenes is the real story. This story is one of high growth, huge challenges and an enormous opportunity ahead of us. It began with our founder Will, arriving in London over 5 years ago and finding it almost impossible to order great food, despite the wealth of incredible restaurants in the city. Fast forward 5 years and we operate in 13 countries with over 50,000 riders who deliver orders from 50,000 restaurants in over 200 cities worldwide.
We want to be the definitive food company - the app you go to any time you have a hunger pang. We are transforming the way people think about food. We are providing people with limitless access to different cuisines and restaurants, turning cooking from a chore to a choice, and giving people the freedom to eat what they want, when they want, where they want it.
We work with riders, restaurants and consumers. We operate one of the most complex three sided marketplaces in the world and we do this in real time. Millions of customers and thousands of restaurants and riders rely on us to match them within milliseconds. The algorithms behind that marketplace are the secret sauce that allow us to deliver our orders in under 30 minutes.
And we’re just getting started
The scale of the opportunity ahead of us is immense. The global food market is valued at £7.7 trillion but only 1% of it is currently online. Contrast that with the digital disruption of countless other industries - from banking and travel to retail and communications - it’s clear that our journey in the food sector has only just begun.
Data Scientist, Causal Inference
Whether we’re working to improve our restaurant recommendations or looking to find a more efficient algorithm for routing our drivers, experimentation helps us make the right decisions for our users.
Experimenting at this scale presents some unique challenges and we’re investing heavily in building a world-class platform for designing, deploying, and analysing product experiments. We’re looking for experts in statistical inference and estimation to join our growing team of data scientists and help us develop innovative statistical solutions for industrial-scale experimentation.
Some of the problems we’re working to solve:
- How can we monitor possible interaction effects across our experiments? How can we account for such effects in the analysis of our experiments?
- How can we improve our inference techniques to correctly account for the many statistical tests we calculate? Once we have chosen such a correction, how can we account for it at the power calculation stage?
- How can statistical methods help us estimate the long-term impact of experiments?
- How can we leverage modern statistical algorithms in order to identify any business-relevant heterogeneity of treatment effects?
- How can we avoid running afoul the selection bias across the many experiments we run? Can we use shrinkage estimators to get closer to the actual impact of an experiment once rolled out?
- How can we use the outcomes of previous experiments to improve our inference for a given experiment?
- Investigating complex methodological problems and working collaboratively with a small team of experts to establish world-class standards for experimentation
- Leveraging your broad statistical awareness to proactively identify opportunities to add to and improve our existing experimentation methods
- Prototyping and amending statistical methods to fit our specific circumstances
- Prototyping the code and providing clear communication and written documentation for the engineering team
- PhD in statistics, economics, econometrics, or a relevant field of applied mathematics
- Broad statistical awareness, including familiarity with frequentist and Bayesian approaches, and a demonstrated ability for developing innovative experimentation and analysis methods
- Familiarity with a scripting language, some proficiency with Python would be an asset
Life at Deliveroo
We are a growing team, with very large impact, seeking to answer some of the most interesting questions out there. We move fast, we’re always looking for new ideas and we’re very transparent about the decisions we make and why we make them.
There are so many questions we need to answer and plenty more we haven’t even encountered. How do data and technology help restaurants to grow as consumer habits change? How can we predict what someone wants to order for dinner long before the idea has even crossed their mind? At Deliveroo these are just some of the tough problems we are solving - and there is no challenge that cannot be yours. No solution is owned by a particular team, which means the scope for growth and personal impact is enormous.
Benefits and Diversity
At Deliveroo we know that people are the heart of the business and we prioritise their welfare. We offer a wide range of competitive benefits in areas including health, family, finance, community, convenience, growth, time away and relocation.
In 2018 we announced our decision to give every employee equity in the company. We did this because we wanted all of our employees, regardless of location, level or role to be owners and because we believe that this is the right thing to do. We believe this helps build a culture where everyone is committed and able to share in the company’s success.
We believe a great workplace is one that represents the world we live in and how beautifully diverse it can be. That means we have no judgement when it comes to any one of the things that make you who you are - your gender, race, sexuality, religion or a secret aversion to coriander. All you need is a passion for (most) food and a desire to be part of one of the fastest growing start-up’s around.