Data Scientist

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 (maternity leave of at least 6 months) 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

• New ML opportunities get identified and proven out before engineering time is spent on them, because you research, prototype, and validate the model first.
• 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.
• Models keep working after they ship, because you own the full lifecycle: development, production deployment, drift monitoring, and retraining as the data changes.

What you Bringg

• 3+ years' experience as a Data Scientist, working with Python, SQL, and the standard data science toolkit (Jupyter Notebook, Pandas, scikit-learn, TensorFlow, PyTorch)
• BSc in an exact science: mathematics, computer science, or statistics
• Experience building prediction and clustering models using both supervised and unsupervised methods
• Proven ability to own the algorithm/data science lifecycle end to end, from idea to production
• Experience running models in production: feature/prediction drift analysis, alerting, and updating models to work with the latest data
• Familiarity with the MLOps lifecycle
• Comfortable using AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) to speed up experimentation and iteration
• 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
• Comfortable working independently on abstract, loosely-defined problems in a fast-moving, agile environment

Good to have

• Experience with routing and navigation algorithms
• Experience with Vertex AI or an equivalent cloud ML platform (training, deployment, monitoring)
• Experience engineering geospatial/location-based features (geohashing, lat/lng, zip-code and polygon-based features, geofencing) for real-world prediction models

Why Bringg

• At Bringg, your work runs infrastructure that the world's largest retailers depend on. The product is complex, the customers are demanding, and the stakes are real.
• The people here are self-directed, curious, and show up when it matters. You won't get a full map, but you won't be alone figuring it out.
• Worth Showing Up For.