Data Science Lead

Houseful

Data Science Lead building and leading data science capability at Alto Software Group. Overseeing predictive modeling and collaborating with engineering and commercial teams.

Posted 6/23/2026full-timeLondon • 🇬🇧 United KingdomSeniorWebsite

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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 ThoughtSpot 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.

Requirements

What you’ll need

**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 SaaS 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.

Benefits

Comp & perks

**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**

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonSQLpredictive modelingstatistical analysiscausal inferencedata segmentationscoring frameworksdata qualityfeature engineeringautomation

Soft Skills

accountabilitycommercial awarenesscross-functional collaborationoutcome-focusedproblem-solvingmentoringcommunicationprioritizationadaptabilityanalytical thinking