Senior Specialist, Data Science & Artificial Intelligence II

Key Accountabilities

• Develop, test, and validate machine learning, deep learning, and Generative AI models (including LLM-based applications).
• Implement prompt engineering strategies and retrieval-augmented generation (RAG) pipelines.
• Perform feature engineering, model tuning, and performance optimization.
• Prepare, cleanse, and transform structured and unstructured datasets.
• Support deployment of ML and GenAI models using MLOps and LLMOps practices.
• Conduct structured evaluation of LLM outputs including hallucination detection and quality scoring.
• Integrate AI solutions via APIs into enterprise systems.
• Document model design, assumptions, risks, and validation results.
• Ensure compliance with data governance, cybersecurity, and ethical AI guidelines.
• Support monitoring, retraining, and lifecycle management of deployed models.

Skills:

• Python, SQL, ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Prompt engineering
• RAG pipelines & vector databases
• Model fine-tuning and evaluation
• Data preprocessing & feature engineering
• Basic cloud deployment concepts
• MLOps / LLMOps fundamentals
• Analytical problem-solving
• Results Orientation
• Collaboration
• Continuous Improvement
• Accountability

Minimum Qualification

• Bachelor s degree in Data Science, Artificial Intelligence, Computer Science, or a related quantitative field

Minimum Experience

• 4 6 years in data science, machine learning, or applied AI roles.