Senior Data Scientist
4 days ago
JOB DESCRIPTION
Experience :
4 - 7 Yrs
Location :
Bengaluru
Designation :
Senior Data Scientist
Role Overview:
As a Senior Data Scientist specializing in NLP and ML, you will lead the design, development, and optimization of advanced AI applications, with a special focus on NLP and LLMs. You'll tackle diverse NLP use cases, contribute to ML models for credit scoring and risk assessment, and drive research and innovation in large-scale transformer models.
Key Responsibilities:
- NLP & LLM Model Development: Build, fine-tune, and deploy advanced NLP models—including text classification, document analysis, entity recognition, and sentiment analysis—leveraging state-of-the-art architectures (BERT, GPT, Llama, etc.).
- LLM Research & Customization: Explore, adapt, and optimize pre-trained LLMs (e.g., OpenAI, Hugging Face, Llama).
- Credit & Risk Analytics: Develop, refine, and evaluate ML models for credit scoring, scorecard generation, and risk analytics.
- Data Exploration & Processing: Analyze and preprocess large amounts of unstructured text using tokenization, language normalization, embeddings, and vectorization.
- Deployment & Integration: Collaborate with engineering/product teams to integrate NLP/ML/LLM solutions into real-world products, ensuring scalability and reliability.
- Continuous Innovation: Stay current on advances in NLP, ML, and generative AI, proactively translating research breakthroughs into practical applications.
- Mentorship & Collaboration: Guide junior team members and collaborate across data, product, and engineering groups.
Required Skills & Experience:
- Work Experience: 3–4 years as a data scientist, NLP engineer, or ML specialist with hands-on experience in NLP and LLMs.
- NLP & Deep Learning: Proven expertise in NLP tasks (text classification, entity recognition, semantic analysis) and deep learning, especially with transformer architectures.
- Large Language Models: Experience working with, training, and deploying LLMs (GPT, Llama, BERT, etc.).
- ML Frameworks: Advanced skills in Python with frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and Keras.
- Tooling: Experienced with libraries (NLTK, spaCy, scikit-learn, NumPy, pandas, OpenAI API).
- Database & API Integration: Proficient with SQL/NoSQL databases and RESTful API development/integration.
- Problem Solver: Strong analytical, debugging, and creative solution skills for real-world ML/NLP challenges.
- Regular Expressions: Hands-on expertise with text processing using regex.
Preferred Qualifications:
- Education: BE/BTech/ME/MTech/MCA in Computer Science or related field (minimum 4-year degree).
- Continuous Learner: Genuine interest in ongoing research and upskilling in AI, ML, GenAI, and computer vision.
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