IDC TECHNOLOGIES (SINGAPORE) PTE. LTD. is hiring for a Senior Data Scientist internship — a 12-month, on-site Software Engineering role based in CECIL STREET, Singapore. It is an unpaid internship. It is open to university students, typically in Year 2–4. Applicants with experience in Machine Learning, Currency, Dynamics, Pipelines, and Experimentation are a strong fit.
About this role
Job Duties & Responsibilities: • Work with large and complex financial datasets to develop end-to-end data science solutions for pricing various financial products, dynamic campaign optimization, and customer personalization. • Conduct research and literature review to assess and evaluate trade-offs between different quantitative algorithms and models. • Implement and train AI/ML models and optimize algorithm efficiency (GPU distributed computing, concurrent programming) • Refactor and document code into reusable libraries/ APIs/ tools, deploy machine learning ecosystems, and perform sub-system integration as required. • Integrate solutions into enterprise MLOps ecosystem and automate CI/CD pipelines for model lifecycle maintenance and monitoring. Requirements: • Good understanding of the data science production life cycle with demonstrable experience working with structured, semi-structured and unstructured data. • Excellent software skills (Python, SQL variants) and knowledge in design patterns, code optimization, object-oriented programming. • Experience applying quantitative and machine learning algorithms for pricing and marketing. • Demonstrable expertise in some of the following domains - econometrics, statistical modelling, time-series analysis, signal processing, reinforcement learning, estimating causal relationships/ counterfactual effects, dynamic pricing. • Solid understanding of foreign exchange markets, including knowledge of currency pairs, market dynamics, and key drivers. • Hands-on experience in designing and executing digital campaigns and experimentation (A/B, Multivariate, Bandits, Sequential, quasi-experiments), evaluation methodologies (DiD variants), and conducting experiments to optimize campaign performance.
Also in Software Engineering