Data Analyst

Responsibilities:Tencent is a world-leading internet and technology company that develops innovative products and services to improve the quality of life of people around the world. Founded in 1998 with its headquarters in Shenzhen China, our guiding principle is to use technology for good.
We are not only a major video game publisher in the world, we also produce other high-quality digital content, enriching interactive entertainment experiences for people around the globe. We offer a range of services such as cloud computing, advertising, FinTech, and other enterprise services to support our clients’ digital transformation and business growth.

Level Infinite is a global gaming brand dedicated to delivering high-quality and engaging interactive entertainment experiences to a worldwide audience, wherever and however they choose to play. It operates from bases in Amsterdam and Singapore with staff around the world.
To learn more about Level Infinite, visit www.levelinfinite.com, and follow on Twitter,Facebook, Instagram and YouTube.

Responsibilities

1. Work collaboratively with Product and Engineering teams to identify key risks, understand high value users and uncover insights by using data analytics (e.g. requirement understanding, data sourcing, data quality check, data cleansing, data pre-processing, logic development, model development, and data visualization).

2. Develop and perform ETL and automation, define and evaluate metrics, monitor key product metrics and their progress against goals, and understand root causes of changes in metrics.

3. Explore opportunities broadly with open mindset and leverage various data science methods flexibly, in order to identify high-impact opportunities, initiate project ideas, prototype solutions, and drive project completion

Requirements:

Requirements

1.Bachelor’s degree or above in Computer Science, Machine Learning, Statistics, Economics, Mathematics or equivalent technical field.

2. 4+ years of experience in custom ETL design, implementation and maintenance.

3. Experience programming in SQL, Python, R, or related language.

4. Experience with Big Data technologies such as Hadoop, Hive, Spark, Flink, etc.

5. Good data visualization skills using Tableau, PowerBI or other visualization tools.

6. 4+ years of experience in applying analytics, inference, experimentation, or machine learning methods in business scenarios preferred.

7. Experience influencing product decisions with data.

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