# Data Scientist - Maternity Leave Cover \(Long-Term\)

- Company: [Bringg](<https://jobstar.asia/company/bringg>)
- Location: TLV
- Team: Product House
- Posted: August 12, 2026

## Job description

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:**

* 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.

## Apply

[Apply on Bringg](<https://job-boards.greenhouse.io/bringg/jobs/8699398002>)

Canonical job page: <https://jobstar.asia/job/data-scientist-maternity-leave-cover-long-term-bringg-tlv-939a5070bc7d3c7d>
