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- Tasks: Lead the development and improvement of our Automated Valuation Model for property valuation.
- Company: Join Houseful, a dynamic company transforming property decisions with data and technology.
- Benefits: Enjoy flexible working, 25 days leave, volunteering days, and wellness perks like gym access.
- Why this job: Be part of a mission to enhance the home moving experience while innovating in data science.
- Qualifications: Advanced degree in a quantitative field and strong Python skills required; machine learning experience preferred.
- Other info: Hybrid role with a focus on collaboration and mentorship within a supportive team environment.
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 pension contribution by the company.
Discretionary annual bonus up to 10% of base salary.
Senior Data Scientist - Hometrack employer: TN United Kingdom
Contact Detail:
TN United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist - Hometrack
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning and data science, especially those relevant to property valuation. This will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with current or former employees of Houseful or Hometrack on platforms like LinkedIn. Engaging in conversations can provide you with insider knowledge about the company culture and expectations, which can be invaluable during the interview process.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully implemented machine learning solutions. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your problem-solving skills.
✨Tip Number 4
Stay updated on the property technology industry trends and challenges. Being knowledgeable about the market will allow you to contribute meaningfully to discussions during interviews and show that you're proactive about understanding the business landscape.
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 Python and machine learning. 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 property valuation processes and how your skills align with Houseful's mission. Mention specific projects or experiences that demonstrate your ability to innovate and solve complex problems.
Showcase Your Technical Skills: Clearly outline your technical skills related to data science, such as experience with libraries like Scikit-learn, Pandas, and Pytorch. Include any relevant projects where you applied these skills, especially in a production environment.
Prepare for Interviews: Be ready to discuss your previous work in detail, particularly how you've tackled data science problems. Prepare examples of how you've collaborated with teams and communicated complex ideas effectively, as these are key aspects of the role.
How to prepare for a job interview at TN United Kingdom
✨Showcase Your Technical Skills
As a Senior Data Scientist, you'll need to demonstrate 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 these skills, and consider bringing examples of your code or models to showcase your capabilities.
✨Understand the Company’s Mission
Houseful is focused on improving the home moving and owning experience. Make sure you understand their mission and values, and be ready to explain how your work aligns with their goals. This shows that you're not just looking for a job, but are genuinely interested in contributing to their vision.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities, especially in relation to machine learning challenges. Think about past experiences where you've identified problems and successfully implemented solutions, and be ready to walk through your thought process during the interview.
✨Emphasise Collaboration and Mentorship
Since the role involves working closely with other data scientists and mentoring junior team members, highlight your teamwork and leadership experiences. Share examples of how you've collaborated on projects and supported others in their development, as this will resonate well with the interviewers.
