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Data Scientist

2 weeks ago

Singapore Carousell Group Full time

Carousell is the leading classifieds group in Greater Southeast Asia on a mission to inspire the world to start buying and 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, Mudah.my, Cho Tot, OneKyat, Ox Street and Refash, serving tens of millions of monthly active users. We have three technology development centers in Singapore, Taiwan, and India, as well as offices in Hong Kong, Malaysia, Philippines, Indonesia, Myanmar, and Vietnam. 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.

**You will**:

- Mine / process data using modern tools and programming languages
- Handle all aspects of ML model development: data wrangling, feature engineering, model selection / architecture, training, offline evaluation, planning A/B experimentation & productionization
- Define and implement models to uncover patterns and power predictions creating business value and innovation.
- Work closely with other data scientists / ML engineers, contributing to the culture of continuous learning & sharing.
- Partner closely with Product Managers & other senior Data Scientists in identifying potential data science solutions to important product / business problems.

**You have**:

- 3+ years exp. as a data scientist / ML engineer, with hands-on experience of solving multiple 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.
- Good programming ability in Python, SQL and experience with machine learning frameworks and libraries (e.g. TensorFlow, Keras, Spark MLlib, Sklearn)