$ 4,000 - 8,000 USD per month
about 1 month ago
- Hiring Bonus$100 USD
- Refer Reward50%Monthly Salary
- Work cross-functionally with business managers/product managers/engineers, and designers
- Develop predictive analytics for customer behaviour and apply machine learning, optimisation techniques, in core subject areas including but not limited to: fraud detection, recommender systems, product understanding, customer segmentation, demand forecasting and supply chain optimisation.
- Build, validate, test, and deploy models and algorithms. Able to implement data science experimental framework to enable organization-wide experiments
- Make strategic data architecture recommendations
- Visualize data for business and technical audiences and Conduct end-to-end data management starting from data collection / preparation to providing insights for key stakeholders
- Effectively communicate solution approaches and analyses to stakeholders.
- Contribute to team’s innovation and IP creation.
- Supervised/unsupervised learning, Classifier algorithms, clustering algorithms, data engineering, feature engineering/optimization
- Knowledges on recommendation system, knowledge graph, nature language processing, image processing and deep learning.
- Strong data visualization capabilities
- A/B testing, bandit optimization, experiment design
- Minimum B.S. degree in Computer Science or a related technical field. Masters or PhD in Computer Science, Statistics, Biostatistics or fields related to data mining preferred
- Excellent communication skills with the ability to identify and communicate data driven insights:
- Detail-oriented and efficient time manager who thrives in a dynamic and fast-paced working environment
- 2+ years of Python and/or R development and Unix/Linux system experience
- 2+ years of SQL (Mysql, Mssql, PostgresQL, Hive, etc) experience
Preference will be given to candidates with the following additional requirements as below:
- Working experience on big data analytics and distributed databases or distributed systems (Hadoop, Spark, Hbase, Cassandra etc.)
- Working experience with parallel algorithms in data modeling / machine learning