Machine Learning expert for a large financial institution.
- Design solution architectures for data science/machine learning products and ensure its production quality from data-ops perspective.
- Work alongside Technology team to translate successful data science/machine learning proofs-of-concept into production-grade solutions for deployment.
- Build solid end-to-end pipeline from raw data ingestion, storage to model servicing and inference for both batch and stream processing.
- Establish proper monitoring of online/offline models and perform re-training whenever necessary, preferably through an automated procedure.
- Facilitate machine learning model experiments at scale.
- To support and inspire data scientists and data analysts in writing high-performance, modularized, and reproducible codes.
- Keep track and evaluate cutting edge technology and industry trends in the field of machine learning model deployment and operation.
- Minimum Bachelor/Postgraduate in Statistics, Mathematics, Engineering, Computer Science or a related field.
- Minimum 3 - 5 years of working experience in machine learning model deployment and operation in production scale preferably with good knowledge in big data platforms.
- Strong competence in software programming using Java/Scala/Python and a variety of both traditional relational databases and modern distributed file systems.
- Familiarity with Apache Spark (and/or any other mainstream distributed computing platform) and the Hadoop eco-system (including but not limited to Hive, Hue, HBase, etc).