Data Scientist And AI Lead

AI Platform and internal model development

• Lead the design and development of an enterprise AI model using internal company data that delivers actionable insights and automated alerts.
• Build intelligent monitoring and exception-detection capabilities across SAP, ecommerce, IT security and other business applications.
• Establish scalable pipelines for continuous data ingestion, model training, evaluation and deployment.

Business Understanding & Problem Framing

• Engage closely with business teams to understand objectives, pain points, KPIs and decision workflows.
• Translate business requirements into structured AI/ML problems using strong analytical and consulting skills.
  
• Explore and analyse datasets to uncover hidden patterns and develop hypotheses that shape AI solutions.

Generative AI, NLP & LLM Development

• Lead development and deployment of Generative AI, NLP and LLM-based solutions tailored to business use cases.
• Build POCs and scalable solutions across functions such as operations, finance, supply chain, e-commerce, customer service and IT.
• Apply fine-tuning, prompt engineering, vector databases and domain-specific adaptation techniques.

Stakeholder Interaction

• Prepare and present solution proposals, models, dashboards and POCs to leadership and key stakeholders.
• Clearly articulate the impact and feasibility of AI solutions using storytelling and data-driven narratives.
• Demonstrate the relevance and effectiveness of Generative AI applications across multiple business domains.

Engineering, Cloud & MLOps Integration

• Integrate AI and ML models into enterprise systems across Azure, AWS, GCP or on-premise environments.
• Work closely with application, DevOps and IT teams to build robust MLOps pipelines ensuring automation, monitoring and lifecycle management.
• Oversee continuous improvement, productionisation and scaling of AI solutions.