Senior Specialist, Data Science & Analytics II

Job Purpose

Design, develop, and deploy machine learning and Generative AI solutions to solve defined business problems, ensuring technical robustness, model performance, and responsible AI implementation.

Key Accountabilities

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Develop, test, and validate machine learning, deep learning, and Generative AI models (including LLM-based applications).

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Implement prompt engineering strategies and retrieval-augmented generation (RAG) pipelines.

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Perform feature engineering, model tuning, and performance optimization.

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Prepare, cleanse, and transform structured and unstructured datasets.

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Support deployment of ML and GenAI models using MLOps and LLMOps practices.

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Conduct structured evaluation of LLM outputs including hallucination detection and quality scoring.

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Integrate AI solutions via APIs into enterprise systems.

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Document model design, assumptions, risks, and validation results.

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Ensure compliance with data governance, cybersecurity, and ethical AI guidelines.

• Support monitoring, retraining, and lifecycle management of deployed models.

Minimum Qualification, Experience and Competencies

• Minimum Qualification

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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.

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