Senior Data Scientist (Maternity cover)

Global-e Online Ltd.; Dublin; On-site; EUR 110,000 - 140,000; Full time

Job summary

Global-e Online Ltd. is seeking a Senior Data Scientist to drive the world’s first machine learning–based, highly accurate classification system for cross-border trade.

You will design and deploy ML models and LLMs, work with NLP techniques, and translate data into strategic decisions that improve product and customer experience. Role requires 5+ years in data science, end-to-end ML lifecycle experience, and strong coding and mathematical foundations.

Qualifications

• 5+ years of data science experience solving real-world problems.
• Experience with end-to-end data product lifecycle from ideation to production.
• Experience training, fine-tuning, and deploying LLMs.
• Experience with NLP algorithms and taxonomy/recommendation/search domains.
• Strong programming skills and mathematical foundations for ML.
• Experience with transformer architectures (BERT, GPT) for classification.

Responsibilities

• Research, design, maintain ML models for fast, accurate classification.
• Develop and deploy LLMs to enhance accuracy and automation.
• Explore data to identify trends and model approaches.
• Use model outputs to deliver commercial impact and customer value.
• Collaborate with product and engineering to inform decisions with data.
• Document insights for stakeholders to drive actions.
• Continuously evaluate and improve model performance.

Skills

Data science

ML models

NLP

Transformer architectures

Communication

Tools

Python

TensorFlow

PyTorch

LLMs

Job description

We are looking for a Senior Data Scientist to join our classification team. A critical component to enabling cross-border is delivering seamless clearance through customs. This is also an incredibly challenging problem where Global-e has radically changed the industry by delivering the world’s first machine learning-based, highly accurate classification system that replaces the need for people to inspect and classify individual products. This capability enables our clients to ship goods from anywhere in the world to anywhere in the world directly from their stores and fulfillment centers, keeping customers happy with fast and seamless delivery.

Main Responsibilities:

• Research, design, maintain, and evolve the company’s machine learning models to support the world’s fastest and most accurate classification and restriction systems for cross-border trade.
• Develop, fine-tune, and deploy Large Language Models (LLMs) to enhance classification accuracy and automation capabilities.
• Engage in both exploratory data analysis to identify trends and formulate modeling approaches to solve problems
• Use model outputs to deliver both short-term commercial impact and longer-term business value and customer experience
• Partner closely with product, engineering and other business leaders by providing consulting and analytic services that help influence product decisions with data
• Document clear insights and analysis for stakeholders to understand and take actions accordingly
• Continuously evaluate model performance and drive iterative improvements to enhance accuracy and effectiveness
• Help cultivate a culture of experimentation through sharing of best practices and trainings

Requirements

• At least 5 years of experience in data science, solving real-world problems, and using modern technologies to develop ML models.
• Experience with the full lifecycle of a data product – ideation to productionizing and iterating.
• Experience with training, fine-tuning, and deploying LLMs, as well as applying state-of-the-art architectures to domain-specific challenges.
• Experience with NLP algorithms and approaches and their applications to taxonomies, recommendations, and search domains.
• Solid programming skills to code, build, and test models.
• Knowledge of and appetite for mathematical principles that are the foundation of ML methods.
• Familiarity with transformer-based architectures (e.g., BERT, GPT) and their application to classification and predictive modeling.
• Experience in optimizing and scaling deep learning models for real-world deployment in production environments.
• Excellent communication skills, both written and verbal; the ability to convey your message to team members and other stakeholders