Job Opportunities API

Senior Data Scientist Who we are: Founded in 2003, Mobysoft provides data-based insight solutions to a wide range of social housing clients, through market-leading products, simultaneously helping keep tenants housed in homes they can enjoy and improving social housing landlords long term organisational health. Our vision is a world in which intelligent technology significantly improves the quality of life for people who live in social housing and our mission is delivering accurate actionable data insights that help social housing providers ensure a consistent, equitable service. What are we looking for? We are an ambitious, customer-centric, hybrid-working Data & Analytics team, dedicated to developing a new generation of data products that unlock significant value for the social housing sector. We operate with a focused product lens, driven by curiosity and a commitment to technical excellence. As a Senior Data Scientist you will take deep, structured/tabular problems – rent arrears, tenant risk, contact strategy, repairs history – and work them through to clear, evidence-based outcomes. Alongside our existing senior data scientist (who leads on natural language processing [NLP] / and neural networks [NN]) you will be part of a small, central function that partners closely with product and engineering teams on a single, shared roadmap, with a one-team mentality throughout. We take a test-and-learn approach: real experiments, time-boxed and honestly evaluated, each ending in a clear call to do more, ship what we have, or stop. We’re looking for an accomplished data scientist with strong foundations, deep structured-data experience, and the judgement to apply the right level of complexity – from simple, robust baselines to more advanced methods where they add clear value. Key Responsibilities What will you be doing? Our direction of travel includes: · Early-warning and lifecycle modelling. For rent, distinguishing genuine tenant arrears from technical or timing artefacts, and tracking cases from early warning signs through to resolution, stabilisation, or support; for properties, detecting risks, and understanding the balance between planned and responsive repairs. · Forecasting. Forecasting rent payment patterns, balances, and repairs/asset needs over time – for example which property cohorts to prioritise for planned repairs – using both classical and modern time-series methods. · Contact strategy. Designing contact strategies that focus limited capacity on where it can make the most difference across channels including human, AI-assisted, and SMS. · Prescriptive analytics. Linking model outputs to prescriptive, next-best-action recommendations. For example, root cause analysis to help get first-time fixes right on repairs. · AI agents. Designing, building, and deploying AI agents that combine our own data with external reference sources to support faster, better decisions. · Deployment & monitoring. Deploying and monitoring machine learning (ML) models in production, with the engineering discipline to catch drift and issues early. · Cross-team support. Occasional collaboration on NLP/NN-related work led by our existing senior data scientist, providing cover when needed. · What's next. Plenty that hasn't been thought of yet. This list will evolve alongside our business, the role and your findings, insights and ideas. In short, there will be lots to keep you interested, opportunities to keep your technical and interpersonal skills developing, and a real chance to drive innovation and change. This is a professional, technical role with no line management responsibilities. There will be multiple opportunities to take technical ownership of, and lead the delivery of, specific data science workstreams. Qualifications and skills Required What qualifications and experience are we after? · A Master's or PhD in Data Science