Data Scientist, Fulfilment

Nivoda

full-time

Posted on: 4/8/2026

Location Type: Remote

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About the role

Build and iterate on predictive models that move us from ranges (e.g. '3–5 days') to accurate, specific delivery dates
Incorporate hub performance data, team throughput, and routing logic to continuously improve prediction accuracy
Develop and own demand forecasting models for Express offerings across diamonds, melee, gemstones, and jewellery
Determine optimal inventory levels by hub and product type to meet demand without overstocking
Identify opportunities to reduce lead times and improve fulfilment accuracy across the network
Partner closely with data engineering team to define data requirements and build robust pipelines
Surface actionable insights to the Fulfilment org to drive speed and accuracy — two of the company's three core pillars (quality, speed, price)

5 - 7+ years of experience as a data scientist, with a strong track record of building and deploying predictive models in production
Proficiency in machine learning, statistical modelling, and forecasting techniques
Ability to work highly autonomously — you own your work end-to-end without needing close supervision
Strong collaboration skills; experience working with data engineering teams to translate model requirements into data infrastructure
Comfortable operating in ambiguous, fast-moving environments
Preferred Qualifications
Background in supply chain, logistics, or fulfilment — experience with replenishment problems, routing logic, or inventory optimisation is highly valued
Experience at companies with complex operational data challenges or similar fast-commerce or on-demand logistics businesses
Familiarity with real-time or dynamic data systems at scale
Physical proximity to one of our hubs (Netherlands or London) — being close to operations helps ground model development in operational reality

Benefits