ST Engineering is a global technology, defence and engineering group with a diverse portfolio of businesses across the aerospace, smart city, defence and public security segments. The Group harnesses technology and innovation to solve real-world problems, enabling a more secure and sustainable world. Headquartered in Singapore, we employ about 25,000 people across our network of subsidiaries and associated companies in Asia, Europe, the Middle East and the U.S., serving customers in more than 100 countries. We rank among the largest companies listed on the Singapore Exchange and are a component stock of the FTSE Straits Times Index, Dow Jones Sustainability Asia Pacific Index, iEdge SG ESG Transparency Index and iEdge SG ESG Leaders Index.
Introduction to Digital Systems Business Area
Digital Systems, a core business area of ST Engineering Group, applies engineering ingenuity and leverages latest digital technologies to develop impactful solutions that enables organistions to thrive in the new dynamic. From Cloud to Software Engineering, Artificial Intelligence to Training Simulation, Advanced Connectivity to Space technologies, our capabilities have empowered numerous organisations to enhance their strategic responsiveness, organisation flexibility and operational effectiveness.
Job Description Summary
- 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 developing and implementing cutting-edge machine learning models and algorithms to solve complex business problems. Your expertise will contribute to enhancing the service delivery of analytics solutions and products to our customers.
Key Job Accountabilities
- 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 enable real-time decision-making.
- Performance monitoring and maintenance: Monitor model performance and address any issues or anomalies that arise. Continuously improve models by refining algorithms, optimizing code, and incorporating feedback from users and stakeholders.
- 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.
- Stay up-to-date with the latest advancements: Keep abreast of the latest research and trends in machine learning and artificial intelligence. Evaluate and recommend new tools, libraries, and methodologies to enhance the efficiency and effectiveness of the machine learning workflow.
Required Experience and Qualifications:
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field. An equivalent combination of education and experience will also be considered.
- Strong programming skills in languages such as Python.
- Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn etc.
- Solid understanding of Statistical Analysis, Probability Theory, and Hypothesis Testing.
- Familiarity with machine learning tools on cloud platforms (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is a plus.
- Experience: At least 5 years’ experience working in a similar role. Hands-on experience in designing, developing, and deploying machine learning models in real-world applications.
- Problem-solving and analytical mindset: Ability to analyze complex problems, break them down into solvable components, and develop innovative machine learning solutions. Strong mathematical and analytical skills are essential.
- Communication and collaboration: Excellent verbal and written communication skills, with the ability to convey technical concepts to both technical and non-technical stakeholders. Proven ability to work collaboratively in a team environment and effectively manage multiple priorities.
- Adaptability and continuous learning: Willingness to adapt to evolving technologies and learn new tools and techniques. Demonstrated commitment to staying updated with the latest advancements in machine learning and artificial intelligence.
- Ang Mo Kio
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|Job Requisition Id
|15 Jun 2023