Toll Group – Data Scientist Intern

Applied Scientist (M.L) Intern, Innovation Lab

Job Description

Position Title: Applied Scientist (M.L) Intern, Innovation Lab 

Business Unit: Toll Global Logistics Department: Innovation

Location: Singapore

Reports to: Data Scientist Lead, Zack Toh, Innovation Lab & Research

 POSITION

The Toll Innovation Lab offers internships that focus on experimenting, prototyping, and delivering breakthrough ideas to create competitive advantages and strategic impacts for Toll and its customers. As an intern, you will have a hands-on interdisciplinary role as an Applied Scientist, with a primary emphasis on exploring the latest advancements in machine learning (M.L) and artificial intelligence (A.I). Your main responsibilities will include conducting research, testing opportunities, and developing cutting-edge M.L and A.I applications for the logistics and supply chain industry, benefiting both internal and external customers. 

This internship is ideal for candidates who have a track record of building software tools, libraries, and applications that integrate scientific research with product development. We are seeking passionate engineers with an adventurous spirit to contribute to Toll's innovation culture and expand their domain expertise within the dynamic and challenging logistics industry. 

 RESPONSIBILITIES

 Modelling and Solution Development Work on the entire lifecycle of machine learning development, including exploring large datasets, experimenting with new algorithms, feature engineering, model testing/training, and offline and online experimentation, including the application of large language models. Support research programs focused on AI/ML areas, such as visual identification, AI bots, robotic and automation systems, etc., leveraging the capabilities of large language models. Design and develop ML/AI applications for industry use cases, utilizing large language models to create innovative solutions that provide a competitive advantage. Develop novel algorithms into prototypes to demonstrate technical feasibility and business value, iterating rapidly using large language models for development and evaluation. 

Design machine learning systems and self-running AI software to automate predictive models, incorporating the power of large language models SKILLS ESSENTIAL TO THE JOB Technical

(Doing skills – job related knowledge, policies, procedures, techniques). Experience programming in Java, C++, Python or related language Machine learning domain knowledge and understanding of various model families, including regression, decision trees, and neural net. Experience with one or more deep learning framework such as Tensorflow, PyTorch or Keras. 

Experience with managing, processing and analysing large, complex, multi-modal and unstructured dataset Software development experience in data manipulation, data mining or prototype development (agile development, software version control, continuous integration, test driven development, pair programming, rapid prototyping) Experience working with containerization Openshift, Docker, prototyping a ML pipeline is desirable. Understanding of mathematical modeling, computer vision, statistical analysis, data mining Experience in at least one of the following fields is desirable 

Natural language processing: text labeling and classification, text understanding, question answering, dialogue systems, entity extraction and reasoning, knowledge graph, etc. Time series modelling: forecasting, anomaly detection Machine learning: deep learning, distributed machine learning, large-scale optimization, Bayesian probabilistic inference Data mining: information extraction, recommender systems, knowledge/pattern discovery, anomaly/churn detection Computer vision: image classification, object detection, segmentation 

Experience in conducting state-of-the-art research and translating research to novel techniques, applying to real world business problems. Personal Demonstrated a Hands-On Approach Exploratory mindset and courage to attempt new ideas 

Team player, as member and creating high performing environment. Thirst for continuous learning and self-improvement. Excellent problem-solving skills Highly adaptable, flexible and able to prevail through uncertainty Excellent communication and documentation skills 

Analytical: Synthesize complex or diverse information; Able to source and prepare data; Design data flows and Data models; Challenge and re-validate conclusions. Design: Apply design principles; Demonstrate attention to details. Problem Solving: Identify and resolve problems in a timely manner; Foresee and communicate potential issues; Develop alternative solutions; Work well in group problem solving situations. Business Acumen: Understand business implications of data for decisions

 QUALIFICATIONS REQUIRED Tertiary: Bachelor's degree in computer science, computer engineering, mathematics, or a related field. 

Master’s degree in computational linguistics, data science, analytics or similar will be advantageous. Professional: 4+ years of experience of building machine learning models for business application