Every year, we help hundreds of thousands of people find rewarding jobs in the ever-changing world of work.
We understand the importance of a job in peoples lifes and we want to help them find work that feels good. And we’ll help them continue to grow as their needs and ambitions change.
At Randstad, our value comes from our people and that is why we put them first. We are proud of our learning culture and career architecture framework that encourages ours team to develop both personally and professionally.
We believe that talent grows when presented with opportunity and this is why we encourage our people to think beyond their role. We have created a culture that enables talent to flourish, encouraging entrepreneurship, fostering team spirit, and continually building mutual trust.
what you will be doing
build ML models: design, train, and deploy scalable machine learning models (NLP, vector embeddings, graph neural networks) to understand resumes and job descriptions beyond mere keywords;
optimization: enhance our semantic search capabilities, ensuring real-time, highly relevant, and unbiased search results for both recruiters and candidates.
mitigate bias: Implement fairness and ethics-first constraints in our algorithms to ensure diverse and equitable hiring practices.
move fast from prototyping in Python to deploying production-grade models in collaboration with our data engineers;
define and appropriate work to the product backlog;
train and coach junior data scientists and interns;
collaborate within the data science community within the Randstad ecosystem, on sharing best practices, harmonizing ML models, and grow collective data science skills
what you will bring
B.Sc. in computer science or related fields (B.Sc. or equivalent experience)
min. 3 years work experience as a data scientist
machine learning (ML) platform: excellent working knowledge of analytical, AI and ML stacks on cloud platforms, preferably on Google Cloud Platform (incl. BigQuery, AI & ML stack) or comparable platforms
ML modeling: strong background in Natural Language Processing (transformers, LLMs, NER) and experience handling unstructured text data.
you know your way around information retrieval systems, learning-to-rank techniques, and vector databases.
high proficiency in Python (incl. relevant libraries and packages) and SQL
ML engineering: experience with the creation of ML pipelines and ML Ops related techniques
Is this the job for you? We would love to hear from you! Please apply directly to the role and we will get in touch with you.
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