Chief AI Strategist

1 day ago

Jaipur, Rajasthan, India beBeeDataScientist Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Lead Data Scientist Role

We are seeking an exceptional Lead Data Scientist to drive innovation in Classical Machine Learning, Conversational AI, and Deep Learning Systems.

  • Develop a comprehensive AI/ML strategy aligned with business objectives.
  • Oversee the research, design, and development of cutting-edge machine learning and deep learning models.
  • Establish best practices for data pipelines, feature engineering, model deployment, and AI governance.
  • Evaluate emerging AI/ML technologies and recommend their adoption where beneficial.
  • Design and implement Generative AI solutions to enhance conversational AI experiences.
  • Optimize Large Language Models (LLMs) for various business applications.
  • Work on text generation, semantic search, intent recognition, and AI-driven recommendation systems.
  • Manage the end-to-end model lifecycle, from data collection and preprocessing to model deployment and monitoring.
  • Implement MLOps best practices to streamline model retraining, CI/CD for ML pipelines, and productionization.
  • Optimize models using hyperparameter tuning techniques.
  • Lead and mentor a team of data scientists and ML engineers.
  • Conduct code reviews, design discussions, and knowledge-sharing sessions.
  • Guide junior team members on best practices in data science, deep learning, and software engineering.
  • Collaborate with stakeholders to integrate AI solutions into production.

Qualifications & Experience:

  • Bachelor's or Master's in Computer Science, Data Science, AI, Statistics, or a related field.
  • 5+ years of hands-on experience in machine learning, deep learning, NLP, and AI-driven applications.
  • Proficiency in Classical ML and Deep Learning.
  • Strong experience with GPT, BERT, T5, Hugging Face Transformers, NLTK, and SpaCy.
  • Programming skills in Python, PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, and MLOps tools.
  • Experience working with large-scale datasets, cloud-based AI solutions, and distributed computing frameworks.
  • Strong understanding of APIs, CI/CD pipelines for ML models, containerization, and model monitoring.

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