We are a “smart warehousing” startup looking for a passionate and talented data scientist to join the founding team and lead the development of our spatial intelligence platform. Our main challenge is to bring automation to warehouse and factory management through real-time data and advanced machine learning techniques.
This will be achieved through the development of features such as:
- Mobile asset utilisation monitoring and optimisation
- Anomaly detection around operator behaviour
- Dynamic vehicle routing
- Space optimisation and strategic stock allocation
Our mission is to increase the safety and efficiency of warehouse and factories by tracking their material handling vehicles (such as forklifts) in realtime. Our high- performance and plug&play indoor tracking sensors can be retrofitted to any machine giving unrivalled visibility of fleet in realtime and at low-cost. This in turn gives managers the insight they need to optimise their operations: right sizing their fleets, saving time by optimising routes and reducing misplaced stock, preventing accidents and cutting costs.
We are an eclectic mix of scientists, technologists and designers on a mission to make material handling operations smarter.
The ideal candidate is expected to have:
• The ability to think and work independently
• Superb team working and communication skills (in English)
• Mathematical fluency (especially stats) and experience with machine learning
• Proficient programmer in Python or similar. Able to prototype and explore data.
• Experience of distributed file systems
• Familiarity with Linux
• A track record of successful projects
• A passion for technology and a desire to push the boundaries (not looking for a 9/5 job)
We are looking to explore different sources of data generated by:
-Our sensors (indoor location, velocity, ID...)
-Onboard vehicle sensors (battery, impacts, GPS, fork heights...)
-ERP/WMS (inventory location, barcode scans, tasks, operator shifts..)