We want to make Houseful more welcoming, fair, and representative. If your background is underrepresented in the technology or property sectors, we actively encourage your application.
Hybrid - Minimum 2 days on-site in London, Tower Bridge HQ
At Houseful, we’re here to help everyone make intelligent decisions about their home.
Do the best work of your life!
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.
We make moves with head and heart to achieve our big ambitions, and to drive progress in the property market. There’s never been a better time to join us.
Hometrack
Hometrack is redefining the mortgage journey for lenders, brokers, and consumers by delivering market-leading valuation and property data services to the financial, property, and technology industries. Our key commercial and go-to-market segment is in financial services, primarily mortgage lenders, including nine of the top 10 mortgage providers.
The role
At Hometrack, we are looking for a talented Data Scientist with demonstrable experience in machine learning. Our Data Science team aims to implement data science into our automated valuation models to ensure we deliver the best products for customers. To achieve this objective, we need your support with:
- 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.
- Ensuring our models perform well in real-world conditions and monitoring their performance over time.
- Work collaboratively with fellow Data Scientists, Analysts and Data Engineers.
- Meeting with stakeholders to translate business needs into data science problems.
Requirements
- An advanced degree in Computer Science, Mathematics, Physics or other quantitative discipline.
- Strong sense of responsibility and a track record of delivering high-quality results in a fast-paced environment.
- Proficient in Python and its associated libraries such as Sckit-learn, Pandas, NumPy, PyTorch, PySpark and LightGBM.
- At least two years experience applying data science to business/real world applications.
- Have some experience with data engineering, building data pipelines with PySpark or SQL to power machine learning applications.
- Comfortable working with version control systems (e.g git).
- Experienced at identifying problems that can be solved with machine learning and delivering them from prototype through to production.
- Great communicator - convey complex ideas and solutions in clear, precise and accessible ways.
If you don’t meet all these requirements but think you would be a good fit for the role, please still reach out!
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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Last updated on Aug 19, 2024