Recycleye
Data Scientist | London
hn · 2-3x/week ONSITE
Jose has strong fundamentals in data engineering, statistical modeling, and Python with proven experience building scalable data platforms (Trino, Elasticsearch, PostgreSQL). However, he's primarily a full-stack and AI engineer rather than a data scientist; his background emphasizes product shipping and real-time systems over deep statistical modeling, anomaly detection, and domain-specific analytics that the role requires. The London onsite requirement and specialized knowledge of waste facility operations/optimization are additional gaps.
Hook: Your background scaling data platforms and building predictive systems at emergency response and ecommerce could transfer well to optimizing recycling facility operations with sensor data and machine learning.
Missing: Statistical modeling and experimental design, Computer vision and sensor data processing (domain-specific), Deep analytics and operational analytics experience, Clickhouse expertise, Manufacturing or waste/recycling domain knowledge, London availability (currently California-based)
Posting
Recycleye | Data Scientist | London | 2-3x/week ONSITE | Mid to Senior level Recycleye and CP Group build recycling plants, and are forming a new team to provide data analytics and optimisation to recycling facility operators. There are optical sorters, AI powered airjets, AI robots and many different types of machines in a waste facility. The waste is constantly varying and the plant can be configured in thousands of ways to sort the material. This team will be collecting this data using different sensors and cameras. We're looking for a data scientist with experience in deep analytics and statistical modelling to understand and visualise the data, and then and model the plant to spot issues before they impact operations, and identify optimistions that make a real difference. We use Clickhouse and Python or Go. Any questions, feel free to email me at peter.fine@recycleye.com