Experienced Data Scientist with over 12 years of experience in Data Science with expertise in planning, designing, implementation of scalable solutions using advanced machine learning, operations research, natural language processing adhering to best practices in python programming, version controlling, MLOps, Cloud (AWS, Azure, and GCP) in the fields of reliability engineering, supply chain analytics and retail analytics Provided technical guidance to the team members on best practices in programming (python, R, sql, and tensorflow), version controlling (git), and cloud adoption (AWS, Azure, and GCP). Defined technical requirements and led the development of MVPs, scalable solutions that continuously improves operational excellence and cost efficiencies. Driven adoption of technical continuous improvement via process improvement initiatives such as MLOps, agile and DevOps capabilities. Contributed to planning, designing, and driving the progress of data science technical excellence plans for the development of new capabilities and gaining insights through advanced analytics to deliver strategic foresight and drive excellence in data science. Contributed to enterprise scale analytics democratisation programme via providing training, coaching, and engagement in the community of practices. Provided and implemented technical guidance across projects in the chosen specialties such as advanced machine learning, operations research, and natural language processing to ensure the right solutions fulfils the business requirements Was responsible for the career progression, performance evaluation, creating personalised development plans for 12 individual data scientists with a different level of experience. Designed and delivered trainings on probability and statistics, supervised and unsupervised learning, reliability engineering, and time series forecasting