Data Scientist II

Job description

You will be joining a central team of talented Data Scientists, working on a wide variety of impactful & important problem areas like: Search, Personalisation, Content Moderation, Trust & Safety, AI led Automation, Computer Vision, Conversation AI (NLP) etc. What you'll do Ship and improve models in production. End-to-end ML model development lifecycle: data wrangling, feature engineering, model selection / architecture, training, offline & online evaluations, planning A/B experimentation & productionization. Turn ad-hoc business needs into solutions, whether that means adapting an existing service or building a new feature. Own your data pipelines: Data preparation, feature processing, training and deployment pipelines your models need. Run and read A/B tests to decide what ships, and explain honestly when a result is noise. Use AI tools as a core part of how you work, to move faster and to raise the quality of what you ship. Work across any of the following domains: Search, Recommendations, Sell Form, Listing Understanding, Trust & Safety Partner closely with Product Managers & other engineers in identifying potential data science solutions to important product / business problems. Work closely with other data scientists, contributing to the culture of continuous learning & sharing. Build multimodal understanding for the sell form, such as extracting attributes from listing photos and text and auto-filling listing details. Improve search and recommendations, from candidate generation and semantic retrieval to ranking and relevance evaluation. Work hands-on with Chinese-language data. Analyse listing text and search queries from Hong Kong and Taiwan directly, in Traditional Chinese and Cantonese as well as English. Requirements 3+ years of applied ML engineering or data science experience, with hands-on experience of solving multiple product & business problems leveraging machine learning. Working proficiency in English and in Mandarin or Cantonese. This role involves hands-on analysis of Chinese-language listing text and search queries from Hong Kong and Taiwan, so you'll need to read and reason about that data yourself. Minimum Bachelor's degree in Computer Science, Statistics, Applied Mathematics or a related quantitative discipline, or equivalent demonstrated experience. Solid foundation in maths, programming and ML/DL fundamentals. Good programming ability in Python, SQL and experience with machine learning frameworks and libraries (e.g. PyTorch, Tensorflow, Keras, Spark MLlib, Sklearn etc.) Good to have : Experience in e-commerce, classifieds or C2C marketplaces, especially with cold-start listings, supply quality or long-tail queries. Experience in one or more of: search, recommendations, marketplace trust & safety, or pricing. Multimodal embeddings and vector retrieval, such as CLIP-style architectures and approximate nearest-neighbour search. Attribute extraction or auto-fill from images and unstructured text. A Master's degree in Computer Science or a related field. Familiarity with Carousell as a user. Knowing the product first-hand helps a lot when tuning feeds and search quality. By proceeding with your application , you are adhering to our PDPA policies. In case you are interested to know more, read about our Candidates Personal Data Privacy Statement . Carousell Group is the leading recommerce group in Greater Southeast Asia on a mission to inspire the world to start selling, and to make secondhand the first choice. Founded in August 2012 in Singapore, the Group has a leading presence in eight markets under the brands Carousell, Cho Tot, Laku6, , OneKyat, Ox Street, and Refash, serving tens of millions of monthly active users. Carousell is backed by leading investors including Telenor Group, Rakuten Ventures, Naver, STIC Investments and Sequoia Capital India. As a team of passionate individuals working together to solve meaningful problems, there is so much more for you to discover in a career with Carousell. Our culture is made up of hiring, developing, and promoting people who embody our values of solving problems for our users; having a mission-first mindset; being relentlessly resourceful; caring deeply; and staying humble to constantly improve. Together as an organisation, we make magic happen.