1 day ago

Data Scientist I

Elsevier

Amsterdam

1 day ago

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Data Scientist I

Data Scientist I role in Amsterdam focusing on NLP solutions and machine learning. Requires Python proficiency, experience with deep learning and LLMs, and 2+ years of experience with a Master's degree. Full-time, on-site position at an information services company.

AIOn-siteFull-timeEntry LevelPythonClassification

Data Scientist I

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AIOn-siteFull-timeEntry LevelPython

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

On-site

Experience Required

2 years

Employment Type

Full-time

Experience Level

Entry Level

Core Qualifications

Technical (Must-have)

PythonClassificationDeep LearningNeural NetworksLarge Language ModelsRandom ForestsLogistic RegressionSVMK-Meansscikit-learnPyTorchTensorFlowPandasNumPyMatplotlibSciPyUnit TestingObject-Oriented ProgrammingGitDevOpsCI/CDAWSAzure

Soft Skills

CommunicationPresentationAnalytical ThinkingProblem SolvingContinuous Learning

Preferred Qualifications

Technical (Nice-to-have)

ParallelizationMulti-threadingSageMakerKubeflowMLFlowApache SparkApache HadoopDatabricksJavaSQLJSONXMLREST APIsMicroservicesUML

Key Responsibilities

•Drive data collection, analysis, and model development with emphasis on classification and deep learning.
•Define quality metrics and assess model performance, presenting insights to stakeholders.
•Craft production-ready Python packages for data science pipelines including preprocessing and model inference.
•Collaborate with technology team for seamless deployment.
•Integrate data science components and conduct quality assessments using LLMs.
•Ensure pipeline resilience against model drift and develop maintenance tools including automated re-training.
•Establish reporting process for pipeline performance and implement automatic re-training strategies.

Data ScientistNLPMachine LearningPythonDeep LearningOn-siteEntry LevelAmsterdamInformation Services

Core Qualifications

Technical (Must-have)

Soft Skills

CommunicationPresentationAnalytical ThinkingProblem SolvingContinuous Learning

Key Responsibilities

•Drive data collection, analysis, and model development with emphasis on classification and deep learning.

•Define quality metrics and assess model performance, presenting insights to stakeholders.

•Craft production-ready Python packages for data science pipelines including preprocessing and model inference.

•Collaborate with technology team for seamless deployment.

•Integrate data science components and conduct quality assessments using LLMs.

•Ensure pipeline resilience against model drift and develop maintenance tools including automated re-training.

•Establish reporting process for pipeline performance and implement automatic re-training strategies.