At a Glance
- Tasks: Lead the improvement of our Automated Valuation Model and innovate with data science techniques.
- Company: Join Houseful, home to trusted brands like Zoopla and Hometrack, transforming property decisions.
- Benefits: Enjoy flexible working, 25 days leave, gym access, and a generous pension contribution.
- Why this job: Be part of a mission to enhance the home moving experience while growing your data science skills.
- Qualifications: Advanced degree in a quantitative field and strong Python skills required; passion is key!
- Other info: Hybrid role with a welcoming culture that values diversity and inclusion.
The predicted salary is between 43200 - 72000 £ per year.
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.
- Designing and creating the pipelines and infrastructure to deploy data science models at scale.
- Creating 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.
- Working 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.
Senior Data Scientist - Hometrack employer: Houseful Limited
Contact Detail:
Houseful Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist - Hometrack
✨Tip Number 1
Familiarise yourself with Hometrack's Automated Valuation Model (AVM) and its applications in the property technology sector. Understanding how the AVM works and its significance in the mortgage journey will give you an edge during interviews.
✨Tip Number 2
Showcase your experience with machine learning applications by preparing examples of past projects where you've successfully identified problems and delivered solutions. Be ready to discuss the entire process from prototype to production.
✨Tip Number 3
Brush up on your Python skills, especially with libraries like Scikit-learn, Pandas, and NumPy. Being able to demonstrate your coding abilities and how you've used these tools in real-world scenarios will be crucial.
✨Tip Number 4
Prepare to discuss your experience with CI/CD processes and MLOps. Highlight any specific tools or frameworks you've used, as this knowledge is essential for deploying data science models at scale.
We think you need these skills to ace Senior Data Scientist - Hometrack
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with machine learning and Python. Emphasise any work you've done in R&D environments and your familiarity with the scientific research method.
Craft a Compelling Cover Letter: In your cover letter, express your passion for improving the home moving and owning experience. Mention specific projects or experiences that demonstrate your ability to innovate and solve complex data science problems.
Showcase Your Technical Skills: Clearly outline your technical skills related to the job description, such as your experience with Python libraries like Scikit-learn and Pandas, as well as your familiarity with AWS or similar cloud platforms. Provide examples of how you've used these skills in past roles.
Prepare for Interviews: Be ready to discuss your previous projects and how you approached problem-solving in data science. Prepare to explain complex ideas in simple terms, as communication is key in this role. Think about how you can convey your understanding of model performance and improvements.
How to prepare for a job interview at Houseful Limited
✨Showcase Your Technical Skills
Make sure to highlight your strong Python experience and familiarity with data science libraries like Scikit-learn and Pandas. Be prepared to discuss specific projects where you've applied machine learning techniques, as this will demonstrate your capability to deliver solutions from prototype to production.
✨Understand the Business Context
Familiarise yourself with Hometrack's mission and the mortgage industry. Be ready to discuss how your skills can contribute to improving the home moving and owning experience. This shows that you’re not just a technical expert but also understand the impact of your work on the business.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with other data scientists, ML engineers, and stakeholders, think of examples where you've successfully collaborated in a team setting. Highlight your communication skills and how you’ve translated complex data science problems into actionable insights for non-technical stakeholders.
✨Demonstrate Continuous Learning
Hometrack values growth and learning, so be prepared to discuss how you stay updated with the latest advancements in data science and machine learning. Share any recent courses, certifications, or personal projects that showcase your commitment to professional development.