Senior Data Scientist

As an experienced Senior Data Scientist with strong expertise in Large Language Models (LLMs), Predictive modeling, and Natural Language Processing (NLP) you will lead advanced analytics initiatives and mentor junior team members.

The ideal candidate will combine a research-oriented mindset with exceptional hands-on Python coding skills and proven ability to communicate complex technical concepts to diverse stakeholders. You should have a track record of delivering impactful machine learning solutions while driving innovation through research and experimentation.

• Design, develop, and deploy advanced machine learning models with focus on LLMs, predictive analytics, and NLP applications
• Lead end-to-end data science projects from problem formulation to production deployment
• Implement and fine-tune Large Language Models for specific business use cases
• Develop sophisticated predictive models for forecasting, classification, and optimization problems
• Build robust NLP pipelines for text analysis, sentiment analysis, entity extraction, and document processing
• Architect scalable ML solutions using modern frameworks (TensorFlow, PyTorch, Hugging Face, etc.)
• Drive research initiatives to explore novel ML/AI approaches and stay current with latest developments
• Prototype cutting-edge solutions and assess their feasibility for business applications

• Master's or PhD in Computer Science, Statistics, Mathematics, Engineering, or related quantitative field
• 5+ years of hands-on experience in data science and machine learning
• 2+ years of experience working with Large Language Models (GPT, BERT, T5, etc.)
• Proven track record of deploying ML models in production environments

• Expert-level proficiency in Python with strong software engineering practices (clean code, testing, documentation)
• Deep expertise in NumPy, Pandas, Matplotlib, Seaborn, Jupyter, and advanced Python libraries
• Extensive experience with TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers
• Hands-on experience with fine-tuning, prompt engineering, and deployment of large language models
• Exposure to text processing, tokenization, named entity recognition, sentiment analysis, and document understanding
• Expertise in regression, classification, time series forecasting, and ensemble methods