Senior Data Scientist - Hometrack...

Hybrid - Minimum 2 days on site in London, Tower Bridge HQ

About Houseful

Houseful is home to trusted brands Zoopla, Alto, Hometrack, Calcasa, Mojo and Prime location. Together we’re creating the connections that power better property decisions, by unlocking the combined strength of software, data and insight.

About Hometrack

At Hometrack, we’re redefining the mortgage journey for lenders, brokers and borrowers. We deliver market-leading valuation and risk evaluation services across the property technology and financial technology industries.

Our customers include 9 of the top 10 mortgage providers, as well as many others in financial services. Founded in 1999, we made our name with our Automated Valuation Model (AVM) and now provide more than 50 million automated valuations every year.

We want to make Houseful more welcoming, fair and representative every day. We’ll consider everyone who applies for this role in the same way, regardless of your ethnicity, colour, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, neurodiversity status, family or parental status, or how long you’ve spent unemployed.

You will be responsible for maintaining and improving the industry leading Hometrack AVM (Automated Valuation Model to estimate the value of residential properties). We are always looking to innovate and better identify and understand what data makes a difference to property value and risk and how to incorporate this into our models and products.

You’ll be at home if you enjoy:

• Being responsible for the performance of our live models. Automating continual retraining and accuracy testing. Detecting model drift and deploying model improvements to ensure the reliability of our valuations for lender clients.
  
• Researching new datasets and advanced machine learning techniques that can be used to increase the accuracy of our property valuation model and improve our AI capabilities across our model and product range
  
• Design and create the pipelines and infrastructure to deploy data science models at scale
  
• Create the tools, frameworks and libraries that will enable the acceleration of our Data Science product delivery and spread the best ML Ops standards across the whole business
  
• Work collaboratively with fellow data scientists, ML Engineers, analysts, product managers and data engineers
  
• Mentoring more junior members of the team on how to solve Data Science problems.
  
• Meeting with stakeholders to translate business needs into data science problems
  
  You’ll hit the ground running if you have:
  
  
• 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 machine learning 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 etc.
  
• Experience using AWS or similar cloud computing platform
  
• Great communicator - convey complex ideas and solutions in clear, precise and accessible ways
  
• Team player who cares about accelerating not only Hometrack’s technical capabilities, but also empowering colleagues
  
  There’s always room to grow and learn with our roles so please don’t be put off if you don’t have all of these skills and experiences. It’s more important that you’re passionate about our mission to improve the home moving and owning experience for everyone.
  
  
• 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
  
• 7.5% pension contribution by the company
  
• Discretionary annual bonus up to 10% of base salary
  
• Talent referral bonus up to £5K
  
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