Data Scientist (User Behaviour)

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Garena

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Job Summary


Job Type
Permanent

Seniority

Years of Experience
Information not provided

Tech Stacks
ETL TensorFlow MLib Oozie PyTorch Apache Spark NoSQL Airflow Scala Hadoop MySQL Python

Job Description

We are looking for Data Scientists who is passionate about data-driven projects that would empower business. You will join a dynamic and fast-paced environment and work with cross-functional teams to elevate business models with best practices in AI Technology and Data Science Products and Services.


• Work cross-functionally with business owners/product managers/developers to uncover insights, build state-of-the-art algorithms and solutions to support business
• Design and conduct data science experimental framework to enable data-driven practice
• Design and implement ETL (extract, transform, load) flows to collect data for supporting business and building Machine Learning(ML) models/algorithms
• Research, build, validate, test, deploy and improve Machine Learning models/algorithms for business optimization, including but not limited to user clustering, classification, regression and recommendation
• Be responsible for the whole lifecycle of ML models/algorithms, from preparing data, building models to publishing models’ output as services/APIs
• Explore data, conduct analysis to extract insights from our data warehouse, which help improve model performance and provide useful findings for business
• Collection & Publishing – more towards engineering (Python/Scala)

Job Requirements

• Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Statistics or relevant fields
• Knowledge of Machine Learning fundamentals: e.g. feature selection, classification, clustering, item recommendation, model validation. Knowledge of ML libraries is a plus e.g. Spark MLib, Tensorflow, PyTorch, XGBoost…
• Working experience with MySQL, NoSQL, proficient in Scala and/or Python
• Experienced in distributed data processing framework: e.g Apache Spark, Airflow/Oozie, Hadoop


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