At a Glance
- Tasks: Lead and build Alto's data science capability, turning rich data into predictive insights.
- Company: Alto Software Group, a B2B SaaS leader in UK housing transactions.
- Benefits: Hybrid work, 25 days leave, wellness perks, and a strong pension contribution.
- Other info: Opportunity to mentor and grow a data science team from scratch.
- Why this job: Shape the future of data science in a dynamic environment with executive support.
- Qualifications: Expertise in Python, SQL, and proven experience in production-level data science.
The predicted salary is between 72000 - 88000 £ per year.
Alto Software Group is a B2B Saa S company that powers more than half of all UK housing transactions each year.
We create software solutions that connect businesses and consumers, delivering a one-stop shop for estate agents and home builders.
Our goal is to drive efficiency, speed up transactions, reduce risk, and improve the end-customer experience.
While we’re not a start-up, we have a start-up mindset and want our people to operate with this mindset so that we can achieve our ambitions.
The Role
We are looking for a Data Science Lead to build and lead Alto’s data science capability from the ground up.
We have rich data flowing through our Mission Control platform and a clear commercial ambition to turn it into predictive insight — this hire gives us the leadership and technical depth to make that happen.
You’ll work at the intersection of data, product, and commercial strategy, with direct access to executive leadership and a platform that’s ready to be exploited.
- What You’ll Do
- Define and own Alto’s data science roadmap, prioritising use cases based on measurable ROI and commercial impact.
- Build, deploy and maintain production-grade predictive models across churn, customer health, propensity and capacity forecasting.
- Design and analyse experiments to test pricing, product and operational changes, raising the standard of statistical rigour across the business.
- Partner with Platform and Data Engineering to productionise models on Mission Control, defining data quality and feature requirements for reliable modelling.
- Develop segmentation and scoring frameworks that Customer Operations and Commercial teams can act on directly.
- Work with the Head of AI Operations to identify automation opportunities grounded in data science outputs.
- Surface insights through Thought Spot and AI-enabled reporting for senior stakeholders, up to executive level.
- Mentor analysts and grow data science capability across the business, building a team rather than a one-person silo.
Who You Are
- A Builder: You don’t just advise on data science — you write production code, ship models, and take personal accountability for outputs that are actually used.
- Commercially
Sharp: You understand Saa S metrics (MRR, churn, NRR, GRR) and have personally connected data science work to measurable business outcomes, not just model performance.
- A Technical
Authority: You bring expert-level Python and SQL, a solid grounding in statistics and causal inference, and a track record of models in production — not just notebooks.
- Cross-Functionally
Effective: You move comfortably between engineering, commercial, and operational stakeholders, translating between data science and business outcomes without losing either audience.
- Outcome-Focused: You prioritise ruthlessly, track ROI on your work, and resist the pull of interesting-but-unactionable projects.
- Comfortable in Ambiguity: You can define the problem as well as solve it — you don’t need a fully formed brief to make progress, and you bring structure where there isn’t any.
- Our Technology Stack
- Languages
- Python, SQL
- BI & Reporting
- Thought Spot
- Platform
- Mission Control (Alto’s internal data platform)
- AI / ML
- Modern ML frameworks; experimentation and causal inference tooling; LLMs and practical AI applications
Why Join Alto?
This is a rare opportunity to build a data science function with a blank sheet, executive sponsorship, and a data platform already in production.
You’ll have the mandate and the access to make data science a structural part of how Alto operates — from retention and pricing to operational efficiency and intelligent automation.
For a technically strong data scientist who wants to lead, not just contribute, this is that role.
- Hybrid — 2 days/week in London HQ
- Everyday Flex — greater flexibility over where and when you work
- 25 days annual leave — plus extra days for years of service
- Day off for volunteering & Digital detox day
- Festive Closure — business closed 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 & private medical
- Gym on-site in London
- 7.5% pension contribution by company
- Discretionary annual bonus up to 10% — of base salary
- Talent referral bonus up to £5K
- #J-18808-Ljbffr
Data Science Lead in London employer: Hometrack
Hometrack is an exceptional employer that champions innovation and collaboration in the financial services sector. With a strong focus on employee well-being, we offer flexible working arrangements, generous leave policies, and comprehensive benefits, including enhanced paternity leave and financial support for fertility treatments. Our vibrant work culture fosters professional growth through continuous learning opportunities, making it an ideal environment for Senior Machine Learning Engineers to thrive and contribute to meaningful projects.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Lead in London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Hometrack.
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We think you need these skills to ace Data Science Lead in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Hometrack, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Hometrack. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Hometrack
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Hometrack!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
