A hybrid Data Scientist role in Richards Bay focused on building and deploying NLP models (text classification, sentiment analysis, NER, topic modeling) to extract insights from text data. Core stack: Python with NLTK, spaCy, Hugging Face Transformers, plus TensorFlow/PyTorch.
Our client is looking for a talented Data Scientist with a specialization in Natural Language Processing (NLP) to join their team in Richards Bay. This hybrid role offers the opportunity to contribute to cutting‑edge projects that leverage NLP to extract insights from textual data, improve customer interactions, and automate complex processes. You will work within a collaborative environment, applying your advanced analytical skills to solve challenging problems. This is a fantastic chance to make a significant impact by developing and deploying sophisticated NLP models that drive business value. You will be instrumental in harnessing the power of language data to unlock new opportunities and enhance decision‑making across the organization.
Key Responsibilities
Develop and implement advanced NLP models for tasks such as text classification, sentiment analysis, named entity recognition, and topic modeling.
Process and analyze large volumes of unstructured text data to identify patterns and insights.
Collaborate with software engineers to deploy NLP models into production systems.
Design and conduct experiments to evaluate the performance of NLP models and algorithms.
Stay current with the latest research and techniques in NLP and machine learning.
Communicate findings and recommendations to technical and non‑technical stakeholders through clear visualizations and reports.
Requirements
Master's or PhD in Computer Science, Linguistics, Data Science, or a related field with an NLP focus.
3+ years of experience in data science, with a strong emphasis on NLP.
Proficiency in Python and NLP libraries (e.g., NLTK, spaCy, Hugging Face Transformers).
Experience with deep learning frameworks (TensorFlow, PyTorch) for NLP tasks.
Strong understanding of statistical modeling, machine learning algorithms, and text representation techniques.
Excellent analytical, problem‑solving, and communication skills.
Benefits
Competitive salary and performance incentives.
Hybrid work arrangement allowing for flexibility.
Comprehensive health and wellness benefits.
Opportunities for professional development and attending industry conferences.
Engaging projects with a focus on innovation and practical application.