Senior ML Data Scientist Real-Time Scalable Models

Catawiki; Randstad; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Stock options

Hybrid work model

Diverse international team

Amsterdam office

Tailor-made trainings

Paid holidays & pension

Job summary

Catawiki is a fast-growing, international tech company based in Amsterdam, offering a hybrid working model and an exciting data-driven environment. As a Senior ML Data Scientist, you will build scalable data products, collaborate with product and engineering teams, and apply advanced ML techniques to real-world business problems.

You’ll deploy models on cloud infrastructure with Kubernetes, work with large-scale data, and contribute to product value and customer experience across our global

Qualifications

• Minimum 5+ years of experience as a data scientist or ML specialist.
• Strong background in statistics and machine learning.
• Fluent Python and SQL skills for data engineering and modeling.
• Experience deploying ML models at scale in production environments.

Responsibilities

• Build production-ready models using ML and data science methods.
• Explore data to identify opportunities and address real-world business problems.
• Deploy scalable models on cloud infrastructure with Kubernetes.
• Collaborate with product, developers, UX, and analysts to improve ML use cases.
• Produce real-time, asynchronous, and batch predictions.

Skills

Python

SQL

Machine Learning

Data Science

Big data concepts

Tools

PyTorch

TensorFlow

LightFM

Git

Docker

Kubernetes

Google BigQuery

MySQL

Spark

Airflow

Kafka

nginx

CI/CD

Job description

Catawiki is a fast-growing, international tech company based in Amsterdam, offering a hybrid working model and an exciting data-driven environment. As a Senior ML Data Scientist, you will build scalable data products, collaborate with product and engineering teams, and apply advanced ML techniques to real-world business problems.

You’ll deploy models on cloud infrastructure with Kubernetes, work with large-scale data, and contribute to product value and customer experience across our global