SR. BUSINESS ANALYST (ANALYTICS)

Primary Purpose Of The Job We are seeking a highly skilled AI/BI Engineer with a strong background in machine learning, AI, and business intelligence. The ideal candidate will be responsible for designing and deploying scalable AI and ML solutions that supports informed decision-making across the organization. You will build and integrate AI-powered applications, particularly those leveraging large language models (LLMs), developing interactive dashboards, integrating LLMs into BI platforms and predictive models to enhance business insights and improve user experience. Required Experience And Skills • Minimum 8 years of experience in Data Science, AI Engineering, advanced analytics, or related roles; Oil and Gas industry experience is a plus. • Experience in developing AI solutions using cloud platforms such as Microsoft Azure, AWS, or GCP, and tools like AI Foundry, Copilot Studio, Vertex AI Studio, and Databricks Mosaic AI. • Design and deploy AI/ML models and LLM-powered applications to support business use cases and enhance decision-making. • Integrate AI/ML models and LLM capabilities into BI platforms to enable natural language querying, automated insights, and conversational analytics. • Evaluate and optimize LLM-generated responses to ensure accuracy and relevance. • Deep understanding of AI/ML algorithms, LLMs, and modern AI architectures. • Proficiency in Python, SQL and AI/ML frameworks such as Hugging Face, LangChain, scikit-learn, TensorFlow, PyTorch and Semantic Kernel etc. • Develop compelling data visualizations and dashboards to support storytelling and real-time insights. • Ensure compliance with data governance, model explainability, and ethical AI practices, including data lineage, access control, and sensitivity labeling. • Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for ML workflows. • Excellent communication skills, with an ability to effectively interact with business stakeholders and articulate complex technical concepts in a clear and understandable manner. Educational Qualifications A bachelor’s degree in computer science, Data Science, Artificial Intelligence, or a related field. Master’s degree preferred, especially with a focus on AI or Machine Learning Show more Show less

Minimum 8 years of experience in Data Science, AI Engineering, advanced analytics, or related roles; Oil and Gas industry experience is a plus. Experience in developing AI solutions using cloud platforms such as Microsoft Azure, AWS, or GCP, and tools like AI Foundry, Copilot Studio, Vertex AI Studio, and Databricks Mosaic AI. Design and deploy AI/ML models and LLM-powered applications to support business use cases and enhance decision-making. Integrate AI/ML models and LLM capabilities into BI platforms to enable natural language querying, automated insights, and conversational analytics. Evaluate and optimize LLM-generated responses to ensure accuracy and relevance. Deep understanding of AI/ML algorithms, LLMs, and modern AI architectures. Proficiency in Python, SQL and AI/ML frameworks such as Hugging Face, LangChain, scikit-learn, TensorFlow, PyTorch and Semantic Kernel etc. Develop compelling data visualizations and dashboards to support storytelling and real-time insights. Ensure compliance with data governance, model explainability, and ethical AI practices, including data lineage, access control, and sensitivity labeling. Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for ML workflows. Excellent communication skills, with an ability to effectively interact with business stakeholders and articulate complex technical concepts in a clear and understandable manner.

The posting outlines responsibilities related to designing and deploying scalable AI and ML solutions, building and integrating AI-powered applications with LLMs, developing interactive dashboards, integrating LLMs into BI platforms, enabling natural language querying and conversational analytics, evaluating and optimizing LLM responses, and ensuring governance and ethical AI practices while communicating effectively with stakeholders.