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Data Scientist II
RELX Group
posted 5d ago
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Flexible timing
Key skills for the job
Job Description
You will be responsible for building, testing and maintaining our NLP solutions. You will work throughout the whole life cycle of data science projects design, implementation, productionisation 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
- Data collection, data analysis, model development, defining quality metrics, quality assessment of models and regular presentations to stakeholders
- 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
- Integration of data science components and end-to-end quality assessment
- 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.
- Establishing the reporting process of the performance of the pipeline, and automatic re-training strategy for the existing pipelines
Requirements
- At least 2 years of relevant applied experience or Msc/MTech in the field of computer science, data science, artificial intelligence, mathematics, statistics, bioinformatics or other quantitative fields with at least 1 years of relevant experience. International working/education experience is a plus!
- Strong hands-on knowledge of Python, ability to write unit tests and production ready code adhering to Python best practices and object oriented programming principles.
- Data processing, cleaning and analysis skills experience with pandas, numpy, matplotlib, boto3
- Experience with SOTA deep learning approaches in NLP domain such as LLMs and finetuning for specific use cases such as named entity recognition and relation extraction
- Affinity with gen AI solutions, various LL models, vectorization methodologies and evaluation of LLMs
- Experience with CI/CD, Git, PyTorch, AWS services such as SageMaker. Experience with Spark/Databricks is a plus!
- Willingness to learn, analytical thinking, problem solving and communication skills; ability to translate complex requirements into practical solutions
- Experience in classical machine Learning Classification, Regression, Clustering, Text Mining. You have an excellent understanding of Neural Networks, Random Forests, Logistic Regression, SVM, K-Means etc.
- Experience in later stages of data science life cycle such as optimizing productionization (techniques such as parallelization, multi threading etc.) and automated model re-training. Interest and affinity in MLOps is a plus!
Employment Type: Full Time, Permanent
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Flexible timing
Monday to Friday
No travel
Day Shift
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