Love buying and selling on Carousell? Then meet the team that handcrafts various parts of the mobile applications, website and backend systems in order to deliver the best user experience. Here at Carousell, our data & engineering teams work on a myriad of problem domains. You get to work with data generated by millions of buyers and sellers & converting them into actionable insights, 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. Every month, we host a range of meetups and talks on different topics, ranging from product hackdays to Data meetups and events!

Ensuring that the user experience stays simple is complicated - and we take pride in our work to keep things that way.

You will be tasked to work on machine learning innovations to help make better predictions of both internal and external ads on Carousell.

Responsibilities:

  • Perform fundamental and applied machine learning in large-scale distributed analysis, streaming data analysis and feature discovery
  • Areas of projects include user/ad modeling, conversion modeling, and modeling new optimization objectives
  • Build, validate, test, and deploy machine learning models (e.g. predictive, forecasting, clustering) using proven and experimental techniques
  • Work with engineering to implement predictive models in production environment
  • Initiate high impact data science projects and with actionable outcomes
  • Provide expertise on concepts for machine learning and applied analytics for the data team and inspire the adoption of data science across the breadth of our organization

Requirements:

  • Experience in ads, neural networks, logistic regression, recommender systems or any large scaled machine learning systems would be highly advantageous
  • Proficient in data science languages/frameworks such as Python, R, Tensorflow

You Are:

  • A self-motivated and independent learner driven by your curiosity in what you may uncover
  • Happy to learn from and share knowledge with team members
  • A doer with a 'get it done' attitude

Good To Have:

  • Experience in building ML models at scale, using real-time big data pipelines on platforms such as Spark/MapReduce
  • Proficiency in implementation of deep learning algorithms (DNN, CNN) in support of: ad ranking optimization and/or ad relevance
  • Please send us your Arxiv, Kaggle and/or Github profile if any!
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