Data Science Lead

Join Houst as they are looking for a Data Science Lead

Who we are:

We’re Houst. A professional management service for properties. Our mission is to make hosting on websites hassle-free for everyone using technology to disrupt the short-term accommodation sector. We’ve grown fast, and continue to do so.

Instagram: @we_are_houst

Twitter: @we_are_houst

Our journey:

Since launching in 2015, we’ve partnered with thousands of happy hosts, helping them to make important earnings. The business has now expanded worldwide – we’re operating in over 20 cities globally, from Auckland to Lisbon, and there’s a lot more to come. From holidaymakers to full-time landlords, host happiness is central to everything we do.

Our Tech team at Houst have built a global platform, our Host Dashboard, that makes it easy for people to share their home. From here, our hosts can track their earnings, update their property’s availability, view and book cleans, view their latest guest reviews and bookings, and get in touch with our host support team, who help our hosts get the most value from their rental property.

We're looking for a data scientist with experience in pricing to Lead our Data and pricing team of 3 at Houst. You will be responsible for taking ownership of our pricing algorithm and ensuring optimal pricing of our property portfolio across all of our markets globally. You will also be responsible for leading and managing data analytics and solutions across all of our business functions and managing a junior Data Scientist and Data Analytics and pricing graduate.


  • Manage full data pipeline from data sources, through BigQuery warehouse and LookML modelling, to business-facing dashboards
  • Maintain existing LookML code and develop new data models to meet business needs
  • Work with different parts of the business to understand their needs and translate into data solutions
  • Support users in building their own dashboards and taking ownership where necessary
  • Present information using data visualization techniques
  • Take ownership of pricing algorithm, designing improvements and working with developers to implement them
  • Run live pricing experiments on property portfolio to evaluate changes
  • Identify data analysis projects, plan and execute analyses, and interpret results using statistical analyses
  • Analyze large amounts of information to discover trends and patterns
  • Build predictive models and machine-learning algorithms
  • Align data projects with organizational goals
  • Experiment with new models and techniques


  • At least 3 years experience in Pricing and Data Analytics
  • Ideally an MSc in Mathematics, Data Science or Data Analytics
  • Previous experience with a start up would be an advantage
  • Knowledge of SQL, Python and/or R
  • Experience with Looker and LookML development would be strongly desirable
  • Strong prioritization and stakeholder management skills
  • Ability to communicate effectively with non-technical business users
  • Understanding of basic statistical methods, particularly hypothesis testing
  • Analytical mind and business acumen
  • Strong mathematical knowledge
  • Problem-solving aptitude
  • Excellent communication and presentation skills
  • Solid understanding of machine learning
  • Knowledge of data management and visualization techniques
  • A knack for statistical analysis and predictive modelling


  • £50,000 - £70,000
  • Enviable company culture – we’ve put time into getting our work culture just right. Regular team social events, company-wide recognition of outstanding work.
  • Hybrid Working (3 days in the London office, 2 remote)
  • Employee discounts – at heaps of restaurants, shops, gym memberships, cinema tickets and more
  • Enhanced Parental Leave – Family comes first. We offer great parental leave to spend time with your new child, regardless of your gender
  • Pension - We provide a pension scheme for all permanent employees, in line with government requirements
  • MacBook – For business use
  • 25 days paid holiday (plus public holidays) – plus an extra day off on your birthday (because who wants to work on their birthday