Data Analyst/ Data Scientist

As a Data Analyst / Data Scientist, you will spearhead the development of robust data solutions and methodologies to drive adoption of advanced analytics in support of Customs’ business goals. You will explore the extensive datasets encompassing international trade flows and traveler declarations in Singapore, utilising modern cloud-based data platform and tools to create impactful solutions that enhance operational efficiency and data driven decision-making across the organisation.

Key Responsibilities: • Design and implement end-to-end AI/ML solutions, from data pipeline development to model deployment and monitoring, using best practices in MLOps and software engineering principles. • Develop and refine data analytical models using various statistical methods, machine learning algorithms, network analysis, advanced search technologies and deep learning approaches to process both structured and unstructured data to solve complex real-world problems such as smuggling detection, risk assessment, and syndicate network identification. • Create interactive web applications and user interfaces that enable stakeholders to interact with data models and visualisations effectively. • Develop and guide the development of intuitive data visualisations and dashboards to improve effective drawing of insights for stakeholders. • Strengthen Customs’ data analytics capability and data-driven culture through documentation of best practices, training delivery and knowledge sharing with junior analysts and business users. • Collaborate with business units and technical teams to operationalise data science and AI projects, while developing long term data analytics strategy and architecture for Singapore Customs.

Requirements 1) At least 3 years of working experience as a Data Analyst / Data Scientist. 2) Expertise in machine learning techniques including supervised / unsupervised learning algorithms, deep learning, model evaluation and validation, and feature engineering and selection. 3) Strong Python programming skills with expertise in key data science libraries on data manipulation, data visualization, and machine learning. 4) Proficient in SQL and databases concepts. 5) Development expertise in one or more of the following domains is advantageous: a. Frontend development b. Network graph c. Advanced search technologies d. LLM applications e. Geospatial analytic tools 6) Relevant industry certifications (e.g. AWS Machine Learning Specialty, IBM Data Science Professional Certificate, Neo4j Certified Professional, DataCamp, Udemy or Coursera) are advantageous. 7) Strong analytical mindset and problem-solving aptitude. 8) Excellent communication and presentation skills, with ability to explain technical solutions to business users and partners. 9) Demonstrated problem-solving ability to proactively address and resolve application issues. 10) Able to handle multiple tasks simultaneously, work independently and as a member of a team.