At Bringg, we're on a mission to transform last-mile delivery into a powerful driver of growth, loyalty, and operational excellence. As an AI-powered SaaS platform, we enable retailers and logistics providers to orchestrate smarter, more efficient delivery operations across every fleet type and service level — from same-day to scheduled delivery. We're looking for a Data Scientist (extended maternity leave cover) to push our ML capabilities further into the platform. Models are already running in production — your job is to make them sharper, keep them honest as the data shifts, and find the next opportunities worth building. This isn't a research-only role. It's an ownership role, end to end. In this role, you will: <ul> <li style="font-size: 12pt;">New ML opportunities get identified and proven out before engineering time is spent on them, because you research, prototype, and validate the model first.</li> <li style="font-size: 12pt;">Complex ideas land clearly across teams, because you can explain a model's logic and tradeoffs to engineers, product, and stakeholders without losing the substance.</li> <li style="font-size: 12pt;">Models keep working after they ship, because you own the full lifecycle: development, production deployment, drift monitoring, and retraining as the data changes.</li> </ul> What you Bringg <ul> <li style="font-size: 12pt;">3+ years' experience as a Data Scientist, working with Python, SQL, and the standard data science toolkit (Jupyter Notebook, Pandas, scikit-learn, TensorFlow, PyTorch)</li> <li style="font-size: 12pt;">BSc in an exact science: mathematics, computer science, or statistics</li> <li style="font-size: 12pt;">Experience building prediction and clustering models using both supervised and unsupervised methods</li> <li style="font-size: 12pt;">Proven ability to own the algorithm/data science lifecycle end to end, from idea to production</li> <li style="font-size: 12pt;">Experience running models in production: feature/prediction drift analysis, alerting, and updating models to work with the latest data</li> <li style="font-size: 12pt;">Familiarity with the MLOps lifecycle</li> <li style="font-size: 12pt;">Comfortable using AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) to speed up experimentation and iteration</li> <li style="font-size: 12pt;">Working knowledge of GenAI beyond coding assistants: prompt engineering and building solutions on top of LLMs/multimodal models, since some of our production problems are solved with an LLM rather than a traditional model</li> <li style="font-size: 12pt;">Comfortable working independently on abstract, loosely-defined problems in a fast-moving, agile environment</li> </ul> Good to have: <ul> <li style="font-size: 12pt;"><span style

Data Scientist - Maternity Leave Cover (Long-Term)

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