Carousell is one of the world's largest and fastest growing mobile classifieds apps with a mission to inspire every person in the world to start selling and buying to make more possible for one another.

Since our launch in Aug 2012, we've expanded into 8 countries with over 250 million listings. 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.

At Carousell you will have the opportunity to improve experience for millions of our buyers & sellers across 9+ markets. Given high volumes of user-generated-content and dynamics unique to a C2C marketplace, there are endless opportunities to generate significant business & user impact leveraging machine learning. 

As a Senior Data Scientist, you will be part of a talented group of Data Scientists, reporting to Head of Data Science. You will get to work with big volumes of data, converting them into actionable insights / models for both our users and team. You will have the autonomy to lead and explore data science projects to solve key business problems, by working together with a core team of passionate data analysts, scientists and engineers. 

You will get the opportunity to work on a wide variety of impactful & important problem areas like: Item Authority, Price Prediction, Content Moderation, Search & Recommendations, Fraud Detection, User Segmentation, Dynamic Ads Pricing & Placement, Chat Analytics (NLP), Image Search etc.

The successful candidate must be able to roll-up his/her sleeves, and work directly with very large datasets and data science tools & libraries. He/she should be passionate about their work, detail-oriented, scientific, and have excellent problem-solving abilities. 

This role also requires a high level of comfort navigating ambiguity, and a keen sense of ownership and drive to deliver results. 

You are expected to embody Carousell’s 5 Core Values: Stay Humble, Solve Problems, Be Mission First, Be Relentlessly Resourceful & Care Deeply

You will:

  • Architect machine learning projects and drive solutioning with desirable outcomes
  • Take end-to-end ownership of solving the problem: data identification, data wrangling, feature engineering, model selection / architecture, training, offline evaluation, productionization
  • Effectively collaborate with product / engineering / data teams across different geographical locations, to implement & maintain machine learning models in production environment
  • Work closely with other data scientists / ML engineers in Singapore and India development centers, contributing to the culture of continuous learning & sharing
  • Independently analyze the research papers related to the problem area and translate relevant ones to working prototypes in an agile manner
  • Partner closely with Product Managers & other senior Data Scientists in identifying potential data science solutions to important product / business problems

You have:


  • 5+ years exp. as data scientist / ML engineer, with hands on experience of solving complex product & business problems leveraging machine learning
  • Good university degree in a quantitative discipline (e.g. Computer Science, Mathematics, Statistics, or related field)
  • Solid foundation in maths, programming and ML fundamentals
  • Strong programming ability in Python, SQL and experience with machine learning frameworks and libraries (e.g. TensorFlow, Keras, Spark MLlib, Sklearn)
  • Experience in building ML models at scale, using real-time big data pipelines on platforms such as Spark/MapReduce
  • Hands on experience of shipping large scale machine learning projects in the Consumer AI space using Deep Learning
  • Diligent and reliable, with excellent analytical skills, communication skills, and teamwork
  • Occasional travel needed


Good to have:

  • MSc or PhD level in a relevant field 
  • Experience of solving Data Science problems related to eCommerce or classifieds space, esp. Involving user-generated-content
  • Experience of solving marketplace related Data Science problems: content discovery, content moderation, fraud detection etc
  • Publications in well-respected conference / journals

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