Senior Data Scientist / Machine Learning Engineer

About ST Engineering ST Engineering  is a global technology, defence, and engineering group with offices across Asia, Europe, the Middle East, and the U.S., serving customers in more than 100 countries. The Group uses technology and innovation to solve real-world problems and improve lives through its diverse portfolio of businesses across the aerospace, smart city, defence, and public security segments. Headquartered in Singapore, ST Engineering ranks among the largest companies listed on the Singapore Exchange. Our history spans more than 50 years, and our strategy is underpinned by our core values – Integrity, Value Creation, Courage, Commitment and Compassion. These 5 core values guide every aspect of our business and are embedded in our ST Engineering culture – from the people we hire, to working with each other, to our partners and customers. About our Line of Business – Mission Software & Services Our  Mission Software & Services  business provides leading-edge mission critical command, control, and communications (C3) systems with secured IT infrastructure and managed services. We support our client’s innovation journey through design thinking, analytics, and AI-enabled decision support with our full suite of cloud computing solutions. We provide intelligent, actionable insights and sustainable solutions to our valued partners in diverse industries including defence, government, and commercial sectors. Together, We Can Make A Significant Impact We are seeking an experienced Senior Data Scientist / Machine Learning Engineer to join our dynamic team. As a Senior Data Scientist / Machine Learning Engineer, you will play a key role in analyzing and presenting data, developing and implementing machine learning models and algorithms to solve complex business problems. Your expertise will contribute to enhancing the delivery service of analytics solutions and products to our customers. Be Part of Our Success Data analysis and insights: Perform exploratory data analysis, generate insights, and present findings to stakeholders. Use statistical methods and visualization techniques to communicate complex concepts and patterns effectively. Develop and deploy machine learning models: Design, build, and optimize machine learning models and algorithms to solve specific business problems. Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models into production environments. Model training and evaluation: Train and fine-tune machine learning models using appropriate algorithms and techniques. Evaluate model performance and identify areas for improvement, employing techniques such as cross-validation, hyperparameter optimization, and ensemble methods. Model deployment and integration: Collaborate with software engineers and DevOps teams to deploy machine learning models into production environments. Implement APIs and integrate models with existing systems and applications to…