Machine Learning / Data Science Researcher - Bristol (Hybrid | 3 days office) Full-time | Permanent Are you a researcher who enjoys solving problems where the solution doesn't already exist? Do you like working at the intersection of machine learning, mathematical modelling, and real-world systems-and want to see your work directly shape commercial products? If so, this could be a strong next step. We're working with a fast-growing B2B SaaS business operating at the cutting edge of behavioural and data science. Their platform helps some of the world's most recognisable consumer brands understand complex human systems and make better decisions from them. They're now looking for a dedicated ML / mathematical researcher to help evolve the core intelligence behind their product. This is a foundational hire in the research function-someone who will shape the next generation of their modelling capability. The Opportunity At the heart of the product is a behavioural and network-based modelling engine that underpins everything the company delivers to clients. This role will focus on improving, extending, and rethinking that engine-bringing in new research, testing novel approaches, and helping translate theory into scalable applied systems. You'll be working closely with the founding team and senior stakeholders, including one of the co-founders (a PhD-level researcher), to ensure research outputs directly influence product direction and commercial impact. This is not a purely academic role, but it does require a research mindset: curiosity, rigour, and a willingness to explore uncharted technical territory. What you'll be doing Researching and experimenting with new approaches to improve model performance Working with complex datasets, including behavioural and network-based structures Evaluating and comparing ML model performance using robust experimental design Incorporating academic research and theory into practical model architectures Designing and testing how model outputs can be applied to real business problems Contributing to the evolution of a core behavioural modelling system Translating research findings into product features in collaboration with engineering Supporting rollout of new capabilities into production systems and customer environments Helping prioritise future research directions based on data, users, and market needs Occasionally supporting external-facing or PR-driven research projects What we're looking for Strong Python skills for ML and data science (e.g. pandas, scikit-learn, Keras) Experience conducting structured research on ML model performance Interest in network science and its real-world applications Ability to define technical problems from ambiguous requirements Strong ability to synthesise research from multiple sources and apply it practically Confidence communicating complex ideas to both technical and non-technical audiences A self-directed mindset-you explore, test, and drive ideas forward independently Strong documentation and experimental discipline Creativity in applying scientific or mathematical theory to real datasets Nice to have Experience building production-ready ML systems Background in marketing effectiveness or attribution modelling Experience with social or network modelling Interest in behavioural science Geospatial or location-based data experience Docker or containerisation experience Linux / Bash familiarity What's on offer Equity / stock options 25 days annual leave public holidays Annual training budget Personal tech allowance Hybrid working (3 days in Bristol office) Opportunity to shape a core product capability from an early stage Why this role? This is a chance to step into a genuinely research-led environment where your work won't sit in isolation. Instead, it will directly influence a live product used by major consumer brands. You'll be joining a small, high-trust team where curiosity is valued as much as execution, and where strong ideas-if they work-can quickly become part of the core platform. If you're someone who enjoys combining theory, experimentation, and real-world impact, this is one worth exploring. Apply by sending your CV to (url removed)