
We are looking for a Data Scientist with strong fundamentals in NLP and machine learning to help build custom AI solutions for real-world talent intelligence problems.
You will work across the stack from data exploration and model development to evaluation and deployment with a focus on building robust, scalable systems using state-of-the-art techniques.
Responsibilities:
- Develop and fine-tune models for NER, text classification, semantic similarity, and clustering
- Work with pretrained embeddings, transformers, and LLMs to extract and normalize structured data from messy text
- Design and run experiments to evaluate model performance and guide improvements
- Collaborate with product and engineering to turn models into robust, production-ready solutions
- Continuously explore research and open-source tools to improve performance and scalability
Requirements:
- 4-7 years of hands-on experience in applied NLP and ML
- Strong coding skills in Python, and experience with Pandas, Scikit-learn, PyTorch or TensorFlow
- Familiarity with modern NLP toolkits: Spacy, HuggingFace Transformers, SBERT, etc.
- Solid understanding of embedding models, attention mechanisms, and evaluation metrics
- Ability to break down abstract problems and build custom, data-driven solutions
Nice to Have:
- Experience with LLM APIs, prompt engineering, or metadata generation using LLMs
- Exposure to knowledge graphs, taxonomy design, or vector databases
- Contributions to open-source NLP tools or research projects
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