Data Scientist

  • Data
  • London, United Kingdom

Data Scientist

Job description


The Plum Guide is on a mission is to build the definitive collection of the world’s best homes. Through expert human curation and innovative tech, we’re taking a scientific and systematic approach to vet every home in every city we open and accepting only the top 1%. Like a modern Michelin Guide - but for homes.

We launched 3 years ago in London. Since then, we have grown 10-20% month on month; expanded to 6 cities; tested over 100,000 homes; developed a customer experience that’s returning the highest NPS scores in the hospitality sector, and are on track to reach over £25M in annualised sales.


We are backed by some of the world’s top VCs and angel investors who have built many of the world’s most exciting companies of today. These include TransferWise, Citymapper, BuzzFeed, Appear Here, Graze, Depop, SoFarSounds, Marvel, GymBox, Threads, Second Home, Zoopla, LoveFilm, Secret Escapes and many more.

We’ve just closed a £14m Series B round of funding. Our focus for the next 12 months is on building an exceptional brand & customer experience and maintaining hyper-growth through an accelerated global rollout. This is where you come in.


The Role


We believe in creating the best experience for our guests and hosts while being able to move fast and operate at scale. This role will have a significant impact in identifying outstanding homes to add to our platforms as we grow and scale across the world.


Additionally, you will improve our guest’s experience of our platform and our communication to them by taking ownership of our search algorithm and helping shape the existing customer journey with detailed insights.


Responsibilities


The main responsibility of being Plum’s 2nd Data Scientist is to create predictive models and analysis that will enable us to scale our acquisition process (which properties to add to our platform), improve our guest experiences and conversion rate. You will take ownership of all aspects of the development process, from concept to production. Finally, you will employ your programming skills to support the data team whenever needed. In more details:


  • Analyse data for insights using a range of tools such as Python, R, SQL and Tableau
  • Turn these insights into solutions that you, the rest of the data team or the tech team can implement rapidly. In particular, you will create predictive models to:
    • classify listings, so that the business can focus on the high priority items.
    • enhance the search algorithm - e.g. personalising what each user sees based on their inherent traits or previous behaviour.
    • attribute marketing spend, what we target users with and enhance where we spend our marketing budget.
  • Move data science projects from concept to fully automated production solutions with the assistance of the Tech team.
  • Present and communicate findings in compelling easy to grasp ways.
  • Enhance our current A/B testing framework and test the model quality.
  • Deliver data solutions that can be embedded in our back and front-end products.
  • Writing code to fetch data from APIs for any new data sources.


Who we are looking for


You don’t need to have prior experience in hospitality or tech startups. The important thing is that you are:


  • Ambitious and with a high standard for what is good enough.
  • You care about getting stuff done. And when obstacles inevitably get in the way, you know how to hustle and think creatively in order to find a solution.
  • Organized - able to project manage complex processes with multiple stakeholders.
  • A self-starting learner, confident teaching yourself to do things you have never done before.
  • Someone who’s a team player and a positive, motivated person to be around.

Requirements

Requirements


We understand that everyone has different experiences and skillsets and just because you might not fulfil all our requirements it doesn’t mean we won’t talk to you. Feel free to reach out and tell us about your Data Science experience and what you can bring to Plum!


  • 1-2 years of experience working as a Data Scientist ideally in startup/scale-up, but corporate positions are also welcome.
  • Master’s or PhD in Statistics, Mathematics, Computer Science or another quantitative field.
  • Excellent coding skills are an asset for this position. Proficiency in Python and experience with SQL are highly desirable. R or Spark are nice extras.
  • Knowledge of a variety of machine learning techniques (clustering, decision trees, neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge of a variety of advanced statistical techniques and concepts (regression, probability distributions, statistical tests, etc.) and experience with applications.
  • High attention to details with a passion for building robust and reliable data sets.
  • Passion to investigate new tools and technologies and develop your existing skillset.
  • Excellent communication skills with a focused and pragmatic approach to delivering results.
  • Experience in writing code to perform simple ETL tasks would be ideal.
  • Experience with data visualization and dashboarding technologies for displaying your results would be a plus.


Benefits


  • An unparalleled opportunity to become an expert in start-up scaling: not only will you lead a city in a VC backed business, but will be coached by some of the best.
  • If you make your objectives happen, you will inevitably be one of the most sought out talents in the startup, hospitality and tech scenes.
  • Genuine influence and control: you will work daily with the founders and management team to shape the company strategy and direction.
  • Be an early team member of what we believe will be one of the most famous startups of the next 10 years.
  • Be part of a passionate, friendly and transparent culture: you will be part of discussions on tech, fundraising, product, brand and global expansion.
  • Competitive salary and potential to be a part of our option scheme: our ambitions are huge and we hope it pays out for all.