3 weeks ago Be among the first 25 applicants

Hybrid Working Pattern - 2 days per week from Tower Bridge office

Zoopla is one of the UK's most instantly recognisable property brands. In fact, we're known and loved by over 91% of the nation (and we're working hard on the other 9%). Our mission is to help the nation make better home decisions - by connecting everyone to their home and giving them personalised insights to help with moving, managing or financing. Over 50 million people visit Zoopla every month to access exclusive data and information on every UK property, search over 500,000 homes for sale and rent, find the best agents and secure the latest mortgage deals.

Recognising the rapid development of AI, Zoopla is investing in Data Science and AI to ensure we remain at the forefront of innovation within the property technology space. When joining our team, you will be instrumental in shaping how AI is utilised not only within Zoopla, but within the industry itself. You'll be designing and implementing cutting-edge Data Science solutions, robust machine learning pipelines, and developing novel AI-driven features that will transform how people find their next dream home. This position offers a great opportunity to work within cross-functional teams, collaborating closely with analysts, software engineers, product managers, product designers, and senior stakeholders. Furthermore, you will play a key role in helping to upskill non-Data Scientists in data science, machine learning and AI best practices.

At Zoopla we recognise that there is always room to grow and learn within our respective roles. Even if you don't have all the desired experiences and skills, please don't be put off from applying. It's more important that you're eager to learn and grow as a Data Scientist and AI practitioner, and are passionate about our mission to improve the home moving and owning experience for everyone. If you have the following, you'll hit the ground running:

• An advanced degree in Computer Science, Mathematics, Physics or other quantitative discipline
• Strong Python experience and knowledge, with the ability to write stable, scalable and maintainable code
• You worked in an R&D environment and/or you are intimately familiar with the fundamentals of the scientific research method: critical thinking, formulating hypotheses, running experiments, drawing conclusions etc
• Experienced at identifying problems that can be solved with data science, machine learning and AI, and delivering them from prototype through to production
• Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps
• Comfortable working with Docker and containerised applications
• Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch, Tensorflow, etc
• Experience designing and and implementing machine learning pipelines
• Experience and expertise in AI and its various components (e.g. embeddings, transformers, MCP)
• Experience designing and and implementing production ready AI applications
• Experience using AWS or similar cloud computing platform
• Experience working with Natural Language Processing and Computer Vision
• A growth mindset, and are passionate about expanding not only your own capabilities, but also your colleagues'.
• Great communicator - convey complex ideas and solutions in clear, precise and accessible ways
• Experience working with cross-functional teams, and being able to collaborate with people of various levels of technical expertise (data scientists, data analysts, software engineers, product managers, senior stakeholders, etc.)
  
  

• Everyday Flex - greater flexibility over where and when you work
• 25 days annual leave + extra days for years of service
• Day off for volunteering & Digital detox day
• Festive Closure - business closed for period between Christmas and New Year
• Cycle to work and electric car schemes
• Free Calm App membership
• Enhanced Parental leave
• Fertility Treatment Financial Support
• Group Income Protection and private medical insurance
• Gym on-site in London - or membership in regional offices
• 7.5% pension contribution by the company
• Discretionary annual bonus up to 10% of base salary

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Industries

  IT Services and IT Consulting

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