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- Tasks: Lead the development and improvement of our Automated Valuation Model for property valuation.
- Company: Join Houseful, home to trusted brands like Zoopla and Hometrack, revolutionising property decisions.
- Benefits: Enjoy flexible working, 25 days leave, wellness perks, and a generous pension contribution.
- Why this job: Be part of a mission to enhance the home moving experience with cutting-edge data science.
- Qualifications: Advanced degree in a quantitative field and strong Python skills required; machine learning experience preferred.
- Other info: Open to all applicants, fostering a diverse and inclusive workplace.
The predicted salary is between 42000 - 78000 £ 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
- 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.
Benefits
- 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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Senior Data Scientist - Hometrack employer: Houseful
Contact Detail:
Houseful 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 mortgage industry. Understanding how this model works and its significance will help you demonstrate your knowledge during interviews.
✨Tip Number 2
Showcase your experience with machine learning and data science tools relevant to the role, such as Python libraries like Scikit-learn and Pytorch. Be prepared to discuss specific projects where you've applied these skills effectively.
✨Tip Number 3
Network with current or former employees of Hometrack or Houseful on platforms like LinkedIn. Engaging with them can provide insights into the company culture and expectations, which can be invaluable during your application process.
✨Tip Number 4
Prepare to discuss your approach to problem-solving in data science, particularly how you identify and address issues using machine learning. Being able to articulate your thought process will set you apart from other candidates.
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 projects or roles where you've worked on model performance, automation, or data pipelines.
Craft a Compelling Cover Letter: In your cover letter, express your passion for improving the home moving experience and how your skills align with Hometrack's mission. Mention specific experiences that demonstrate your ability to innovate and solve complex data problems.
Showcase Your Technical Skills: Clearly outline your technical skills related to the job description, such as your experience with AWS, Docker, and data science libraries like Scikit-learn and Pandas. Provide examples of how you've applied these skills in previous roles.
Prepare for Potential Questions: Anticipate questions related to your experience with machine learning and data science methodologies. Be ready to discuss specific projects where you identified problems and delivered solutions, showcasing your critical thinking and research skills.
How to prepare for a job interview at Houseful
✨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 these skills, especially in an R&D environment.
✨Demonstrate Problem-Solving Abilities
Prepare examples of how you've identified problems that can be solved with machine learning. Discuss the process you followed from prototyping to production, showcasing your understanding of the development life cycle.
✨Communicate Clearly
As a great communicator, you should practice conveying complex ideas in simple terms. Be ready to explain your past work and how it relates to the role, ensuring that stakeholders can understand your contributions.
✨Emphasise Team Collaboration
Highlight your experience working collaboratively with data scientists, ML engineers, and product managers. Share instances where you've mentored junior team members or contributed to a team project, showing that you're a team player.
