Chief Analytics Officer

6 days ago

Hyderabad City Taluka, Pakistan beBee Careers Full time
Lead Data Scientist

As a Lead Data Scientist, you will play a pivotal role in developing AI and machine learning solutions to enhance compliance and risk management processes. Our team is at the forefront of leveraging advanced analytics, AI, and Machine Learning technologies to transform how we manage compliance, conduct, and operational risks across the organization.

This exciting opportunity requires a skilled professional with expertise in designing, deploying, and managing AI/ML models using advanced techniques, including Large Language Models (LLMs) and Agentic AI. You will work closely with cross-functional teams to identify requirements, develop solutions, and deploy models in the production system.

The ideal candidate will have a Master's degree in a quantitative discipline or an MBA with a strong foundation in Computer Science, Statistics, Economics, or Mathematics. At least 12+ years of experience in developing AI/ML solutions, with recent exposure to LLMs and Agentic AI, is required. Proficiency in Python programming, specifically with frameworks like PyTorch or TensorFlow, is also essential.

The successful candidate will possess excellent problem-solving skills, the ability to communicate complex ideas clearly, and thorough knowledge of machine learning concepts, including transformers and language modeling. Experience in data pre-processing, feature engineering, and data analysis is necessary for effective problem-solving in machine learning workflows.

  • Design, deploy, and manage AI/ML models using advanced techniques, including LLMs and Agentic AI.
  • Conduct research on AI techniques to enhance model performance in compliance and risk domains.
  • Collaborate with cross-functional teams to identify requirements, develop solutions, and deploy models in production systems.
  • Communicate technical concepts effectively to both technical and non-technical stakeholders.
  • Analyze and interpret data to evaluate model performance and identify areas for improvement.

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