Full-Time Senior Data Scientist
Elsevier is hiring a remote Full-Time Senior Data Scientist. The career level for this job opening is Senior Manager and is accepting Greece based applicants remotely. Read complete job description before applying.
Elsevier
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About the Role
You will be responsible for building, testing, and maintaining our NLP solutions using (gen)AI technology. You will work throughout the whole life cycle of data science projects: design, implementation, production and beyond. You will deliver efficient and production-ready Python code. You will collaborate with the technology team to deploy and productionize our data science pipelines.
Responsibilities
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Data collection, data analysis, model development, defining quality metrics, quality assessment of models and regular presentations to stakeholders.
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Creating production-ready Python packages for each component of data science pipelines (such as pre-processing and model inference) and their deployment together with the technology team
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Integration of data science components and end-to-end quality assessment.
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Keeping our data science pipelines robust against model drift and ensuring continuous output quality; development of needed tools and strategies for maintenance such as automatic model re-training.
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Establishing the reporting process of the performance of the pipeline, and automatic re-training strategy for the existing pipelines
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Leading and managing projects with a team of data scientists and independently executing the entire small-scale projects
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Consistently communicating team goals and milestone achievements to internal stakeholders
Requirements
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At least 4+ years of relevant applied experience and Msc/MTech in the field of computer science, data science, artificial intelligence, mathematics, statistics, bioinformatics or other quantitative fields or at least 5 years of relevant experience. Phd in the field is a plus. International working/education experience is a plus!
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Strong hands-on knowledge of Python, able to write unit tests and production ready code adhering to best practices and object-oriented programming principles.
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Data processing, cleaning, and analysis skills: experience with Pandas, NumPy, Matplotlib, SciPy
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Hands-on machine learning experience on classification, regression, clustering, and text Mining. You have a good understanding of Neural Networks, Random Forests, Logistic Regression, SVM, K-Means etc., and are a confident user of Scikit-learn, PyTorch and/or Tensorflow.
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Experience in training, building, fine-tuning or evaluating LLMs, and RAG infrastructure is a plus.
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Experience or affinity with vector databases, embedding models is aplus
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Very good communication and presentation skills, in particular proven ability to convey data science concepts effectively to non-technical audiences.
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Proven experience in managing projects and communicating stakeholders
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Willingness to learn, analytical thinking, problem solving skills; ability to translate complex requirements into practical solutions.
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Experience with Git, basic DevOps and CI/CD skills, cloud computing (AWS, Azure), Open Search, Databricks
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Interest and willingness to gain experience in MLOps and data science productionization.