Houseful

Customer Success Manager

• You will be the primary point of contact for a portfolio of higher-value and more complex clients, owning those relationships end to end.
• You will build trusted relationships with senior decision-makers and stakeholders, understanding their business goals and how Alto can support them.
• You will lead regular check-ins, reviews, and business analysis to keep clients satisfied and surface opportunities to add value.
• You will lead contract renewals and identify upsell and cross-sell opportunities to maximise account value and revenue growth.
• You will develop and execute strategies to mitigate churn, identifying at-risk clients and acting proactively to address their concerns.
• You will give consultative advice, showing clients how new features or upgrades solve their emerging challenges.
• You will manage onboarding for new clients, ensuring a smooth and efficient transition onto the Alto platform.
• You will deliver personalised training and resources so clients are empowered to use the platform to its full potential.
• You will troubleshoot early implementation issues and work with internal teams to resolve client queries and technical concerns.
• You will be the voice of the customer inside Alto, relaying client feedback to product and customer success teams to shape future enhancements.
• You will partner with product and development teams to make sure customer needs are addressed in new releases and updates.
• You will work closely with sales, marketing, and support to deliver a cohesive customer experience, and share best practice to help less experienced colleagues grow.
• You will monitor and report on client account health, usage metrics, and satisfaction levels.
• You will turn data into recommendations that help clients improve how they perform using Alto’s platform.
• You will track and manage KPIs such as renewal rates, NPS, and customer engagement.

Customer Success Specialist, Proptech, B2B SaaS

Machine Learning Engineer

• Design, build, and deploy end-to-end machine learning pipelines — from data ingestion and feature engineering through to model serving and monitoring in production.
• Own the full lifecycle of ML models: evaluate, iterate, and retire them with the same rigour you bring to building them.
• Collaborate closely with product and engineering teams to frame business problems as machine learning problems, and translate model outputs into product features users actually understand.
• Establish and maintain standards for ML reproducibility, experiment tracking, and model versioning across the Data team.
• Identify opportunities to apply ML across Alto's product suite — surfacing ideas proactively, not waiting to be briefed.
• Work with large, complex datasets drawn from live UK property transactions, ensuring data quality and feature reliability upstream of every model.
• Contribute to a culture of engineering excellence through code reviews, documentation, and knowledge-sharing with data engineers and analysts.

Senior Machine Learning Engineer

AI Engineer

• Must work from the UK
• Responsible for building the automations and AI integrations that embed AI into operations
• Build, deploy and maintain AI-enabled automations across core systems stack
• Deliver against an internal AI roadmap spanning Customer Operations, Marketing, Finance, Education and Training
• Automate high-volume, manual administrative workflows
• Build AI-enabled workflows in Salesforce, Zendesk, HubSpot, Zuora and Thrive LMS
• Turn the Mission Control data platform into an engine for event-triggered automation
• Reduce operational overhead and improve reporting speed and accuracy
• Build and maintain automation pipelines using n8n, Zapier/Make and direct LLM API integrations (OpenAI/Anthropic)
• Develop API and webhook integrations across Salesforce, Zendesk, HubSpot, Zuora and Thrive LMS
• Implement workflows such as ticket summarisation, tagging, routing and AI triage
• Design and implement RAG pipelines and vector database integrations over internal knowledge
• Develop, test and version prompts; evaluate and improve output quality
• Build event-triggered automations and AI-enabled reporting on Mission Control
• Apply sound engineering standards: error handling, logging and monitoring of automations in production
• Ensure GDPR-compliant, secure handling of customer and company data
• Document solutions clearly and hand over to internal teams for ongoing operation

AI Engineer – Contract

• Map current-state workflows and quantify manual effort and bottlenecks
• Translate findings into clear, prioritised requirements for automation delivery
• Design the taxonomies and knowledge structures that power AI-enabled tools
• Turn scattered documentation into structured, AI-ready knowledge bases
• Audit, clean and restructure existing SOPs, policies and training content for AI consumption, including RAG knowledge bases
• Establish documentation standards: format, ownership and review cadence
• Work with the AI Engineer to ensure knowledge bases serve retrieval pipelines accurately
• Produce SOPs, process maps and RACI documentation where needed
• Support adoption with playbooks and training materials
• Track realised benefits after each automation is deployed

AI Business Analyst, Knowledge Architect – Contract

Data Scientist

• Lead, mentor, and performance-manage a team of analysts — helping them grow their technical and communication skills and creating an environment where they do their best work.
• Set and communicate team priorities across Sales, Operations, Marketing, and Product, exercising clear judgement on urgency and importance when competing demands arise.
• Serve as a strategic thought partner to senior stakeholders, translating business context into analytical direction and making sure the team's output is always tied to what matters.
• Own complex, high-visibility projects that require coordination across the business and SLT exposure — driving them from ambiguous question to clear recommendation.
• Step in at the detail level when it counts: taking analysis from 90% to 100% by working directly in SQL, Databricks, and ThoughtSpot alongside the team.
• Champion the use of AI in analytics workflows — identifying where it adds genuine value and helping the team build fluency with emerging use cases.
• Present findings and recommendations to senior and executive audiences with clarity and confidence, adapting your style to the room.

Head of Analytics

Compliance

• Manage the end-to-end lifecycle of Data Subject Access Requests (DSARs), Right to Erasure (RTBF), and Portability requests — from intake and verification through to fulfilment within the statutory one-month timeframe.
• Perform meticulous reviews of personal data extracts, applying UK GDPR exemptions and carrying out necessary redactions to protect third-party privacy.
• Act as first responder to privacy-related complaints from customers, employees, and third parties, handling each case with empathy and legal precision.
• Support the DPO/Head of Legal in investigating potential data breaches, assessing risk to individuals, and preparing documentation for the ICO where required.
• Maintain and update the Record of Processing Activities (ROPA) under Article 30, ensuring all data flows across the business are accurately documented.
• Support departmental leads in completing Data Protection Impact Assessments (DPIAs) for new projects, tools, and product changes.
• Provide pragmatic, accessible guidance to commercial, marketing, people, and product teams — translating legal obligation into practical action.
• Deliver bite-sized privacy awareness sessions to staff, reducing human-error risk and building a data-conscious culture across the business.

Data Privacy and Compliance Specialist

• 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.

Data Science Lead

Data Engineer

• Help deliver Hometrack's Data Services ambitions by building the best property data sets available
• Inform decision makers by putting the UK’s most trusted property data and insights at the heart of the property ecosystem
• Work with 100s of customers across the property sector ranging from mortgage lenders, house builders, investors, fin & proptech, insurers, telco, retail, and utilities
• Collaborate with colleagues to provide maximum flexibility when matching customers’ needs to the most effective data solution

Senior Data Engineer

Engineering Manager

• Lead our efforts in delivering innovative mission critical products to power property decision making in the UK financial services industry
• Champion our customers and be accountable while mastering our data
• Build connections to collaborate, innovate and deliver together
• Deliver excellence in all deliverables

Data Analyst

• Perform detailed analyses and statistical modelling of property and mortgage data
• Run and process valuations of property portfolios using Hometrack's AVM engine and assist with the analysis and risk modelling of its application
• Compile high-quality reports, typically in a written format or slideware, of a quantitative nature, for mortgage lenders, housing associations and other Hometrack customers and partners
• Contribute to the development, assessment, and ongoing monitoring of the statistical performance of the Hometrack AVM and other models and services
• Build and maintain business intelligence tools (e.g., visualisation reports) to support the commercial and product teams
• Provide clear and accurate answers to client queries that require analytical input and/or support
• Provide support to the rest of the analytics team and wider organisation