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# Data Scientist

- **Company:** Experis
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $90,000.0
- **Contract:** Temporary to permanent
- **Skills:** Java (Programming Language), Artificial Intelligence, Continuous Integration, Elasticsearch, Information Retrieval, Python (Programming Language), Machine Learning, Scrum Methodology, Search Technologies, Software Organization, Large Language Models, Databricks
- **Published:** June 16, 2026
- **Apply:** https://arc.dev/remote-jobs/j/experis-nederland-data-scientist-oxa6y492s6

## About the Role

Must-Have Qualifications

· 3+ years of experience in machine learning and NLP.

· Expertise in information retrieval (semantic search, embeddings), and LLM integration.

· Familiarity with Elasticsearch and hybrid search architectures.

· Strong communication skills to explain complex concepts clearly.

· Ability to balance innovation with compliance and governance requirements.

· Knowledge of common evaluation methods and metrics (nDCG, MAP, MRR).

· Expertise in Python and working in (Databricks) notebooks.

Nice-to-Haves

· Experience with explainability and monitoring of ML models

· Knowledge of CI/CD and software development best practices

· Dashboarding and storytelling for insights

· Affinity with agile working and multidisciplinary collaboration

· Some familiarity with Java is appreciated

## Description

Our Area focuses on creating the best digital experience through a top-notch content platform, intuitive navigation, and powerful search. Your work will impact global websites, apps, and internal tools used by millions of customers and colleagues. As a Data Scientist, you'll also play a key role in ensuring compliance through company's AI Way of Working, guiding the team through stage-gates and governance processes.

Responsibilities

· Develop and train machine learning models for semantic search and personalization.

· Fine-tune and evaluate embedding models and hybrid retrieval logic in Elasticsearch for search solutions.

· Research and implement LLM-based techniques for summarization, metadata generation and other use cases.

· Translate business questions into actionable data products and insights.

· Create clear dashboards and compelling storytelling to communicate insights and teach the team how to do this.

· Collaborate closely with developers, Scrum Master, and Product Owner to scale solutions effectively.

· Support compliance processes (Privacy Impact Assessments, model development plans) within the AI Way of Working.

· Monitor and improve model performance and explainability.


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