Lead Assistant Manager

Role Overview: ;We are seeking a highly skilled and motivated Data Scientist with expertise in model development, model monitoring, and advanced Generative AI (GenAI) / LLM techniques. The candidate will play a pivotal role in building scalable machine learning solutions, fine-tuning LLMs with prompt engineering, and delivering business insights that drive decision-making. The role also requires hands-on experience with modern data platforms, visualization tools, and monitoring frameworks. ;Key Responsibilities: ;Design, develop, and deploy machine learning and deep learning models across business use cases. ;Implement model monitoring frameworks to track model performance, drift, hallucinations, and explainability. ;Work on Generative AI (GenAI) and Large Language Models (LLMs) with prompt tuning, fine-tuning, and evaluation for enterprise applications. ;Collaborate with stakeholders to translate complex datasets into actionable business insights and recommendations. Develop interactive dashboards and visualizations using Power BI and Grafana. ;Leverage Databricks for scalable data pipelines, feature engineering, and model experimentation. ;Write efficient, maintainable, and production-ready code in Python and SQL. Contribute to the development of internal frameworks for model governance, monitoring, and reporting.Partner with cross-functional teams (engineering, product, business) to ensure model solutions align with strategic goals. ;Must-Have Skills & Qualifications : ;Proven experience in machine learning model development, deployment, and monitoring. Strong exposure to GenAI / LLMs (prompt engineering, fine-tuning, evaluation, and safety checks). Proficiency in Python and strong knowledge of SQL. ;Hands-on experience with Databricks for big data analytics and model lifecycle management. ;Working knowledge of Grafana / Prometheus for monitoring and observability. ;Strong ability to generate data-driven business insights and communicate findings effectively. ;Expertise in building dashboards using Power BI or equivalent BI tools. ;Familiarity with MLOps practices, model versioning, and monitoring frameworks. ;Strong problem-solving skills and ability to work in an agile environment. ;Preferred Qualifications (Nice to Have): ;Experience with cloud platforms (AWS, Azure, GCP) for ML model deployment. Knowledge of Lang Chain, Hugging Face, or Bedrock for LLM orchestration. ;Exposure to A/B testing, experimentation platforms, and advanced statistical methods. ;Understanding of responsible AI, fairness, and bias mitigation techniques. ;Educational Background: ; Bachelor’s or master’s degree in engineering (computer science, Data Science, Statistics, Economics, Mathematics or a related field) ;