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Senior Data Scientist, AI
Function
Research & Development
About the Role
The Senior Data Scientist specializing in AI is crucial in driving insights and innovation through advanced data analysis and AI model development. Their expertise is essential for uncovering hidden patterns, making data-driven decisions, and contributing to the organization's strategic goals through robust analytical capabilities.
Responsibilities
- Design and develop robust NLP algorithms and models that can process, analyze, and understand large volumes of text data.
Implement machine learning techniques to improve the accuracy and efficiency of language understanding and generation systems.
Collaborate with cross
functional teams to integrate NLP capabilities into various products and services.
Stay abreast of the latest developments in AI and NLP to ensure the organization remains at the forefront of technological advancements.
Lead the collection and preprocessing of structured and unstructured language data from diverse sources.
Evaluate and improve the performance of NLP systems using appropriate metrics and testing methodologies.
Mentor junior data scientists and engineers, providing guidance on best practices in AI and NLP.
Communicate complex NLP concepts and results to non
technical stakeholders, ensuring clear understanding and support for AI initiatives.
Contribute to the development of patents, research papers, or presentations that showcase the organization's leadership in NLP.
Required Skills
- Advanced degree (Ph.D. or Master's) in Computer Science, Linguistics, or a related field with a focus on NLP or machine learning.
Proficiency in programming languages such as Python, Java, or C++ and experience with NLP libraries (e.g., NLTK, spaCy, Transformers).
Strong understanding of machine learning frameworks (e.g., TensorFlow, PyTorch) and their application in NLP.
Experience with deep learning architectures relevant to NLP (e.g., RNNs, LSTMs, Transformers).
Knowledge of linguistic concepts and text representation techniques (e.g., tokenization, lemmatization, word embeddings).
Excellent analytical and problem
solving skills, with the ability to work on complex issues requiring detailed analysis and evaluation.
Strong communication and collaboration skills, with the ability to work effectively in a team environment.
Familiarity with cloud computing services (e.g., AWS, Azure, GCP) and their machine learning platforms.
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