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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - **Company:** Mobysoft - **Location:** Manchester, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Cloud Computing, Information Engineering, Data Transformation, JSON, Python (Programming Language), Machine Learning, Reference Data, SQL Databases, Parquet, Data Storage Technologies, Feature Engineering, Large Language Models, Deployment Automation - **Published:** July 29, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=a759f158477438a6 ## About the Role * A Master's or PhD in Data Science, ML, AI, or a related quantitative discipline - or equivalent demonstrated commercial experience. * 5+ years of serious commercial experience across complex problems, including transactional/event-level data, with multiple live solution deployments. * Experience working in a test-and-learn way as part of a central data team collaborating closely with multiple product and engineering teams against a shared roadmap. * A track record of committing to and delivering against time-boxed checkpoints, producing concrete, shippable outputs on a schedule. What technical skills are required? Data Engineering Wrangling and engineering data across our warehouse: Ability to source, validate, and shape data - including feature engineering and external/open data - grounded in a desire to genuinely understand the data-generating processes and domain context. Comfortable working across common data formats (e.g. CSV, JSON, Parquet) - loading, inspecting, joining, and aggregating as needed - and understanding what it means for the work when data is slowly changing versus arriving in near real time. Coding * Strong Python and SQL. AI Agents * Ability to design and build AI agents that augment the data science process. For example, an agent that cross-references external reference data against our internal records to distinguish a genuine anomaly from a data artefact., * A background in another regulated or asset-heavy sector - for example financial services, insurance, utilities, or the public sector - that transfers well to this problem space. * General familiarity with neural network architectures and NLP/large language model (LLM) tooling, sufficient to pick up key aspects of a teammate's deep-learning codebase with relative ease and do basic fault-finding when needed - this role is structured-data-first, but should be able to provide occasional cover on the team's NLP/NN work. * Experience working with cloud infrastructure (ideally Amazon Web Services [AWS]) for data storage, training, and deployment., * Works effectively both independently (e.g. during remote deep work) and collaboratively within a team. * Is genuinely curious about where data science and AI are heading, matched with the judgement to weigh new methods against business priorities, timescales, and problem fit. * Communicates clearly, in writing and verbally, including with non-technical audiences. * Works to understand the business context, with a proven ability to align with and actively support business goals, objectives and key results (OKRs). * Looks to build domain knowledge within the sector of application as an intrinsic part of doing good data science. * Is focused on shipping and delivering value, as part of a team that shares that discipline. ## Description 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., 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1520-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)