- Lead the development and validation of high-impact statistical and machine learning quantitative models used to enhance product features and solutions of real-world issues
- Contribute to product design and architecture planning of major systems and features
- Guide and mentor a multi-disciplined Data Science and Data Engineering team to forge a research-oriented and collaborative culture through innovative technology implementation at scale
- Work in a fast-paced environment with tight deliverable timeframes and able to communicate effectively with multiple stakeholders
- Working experience in Singapore needed
- 7 or more years of relevant work experience including at least 1 year of exposure to payments, banking or FinTech
- Minimum Masters or PhD, or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.)
- Advanced knowledge of statistical and machine learning models: Logistic Regression, Support Vector Machines, random forests, XGBoost, Deep Learning models (CNNs/RNNs)
- Proficient in scikit-learn in Python, Pandas, Hadoop, Spark, SQL, etc.
- Proficiency in using Amazon Web Services
- Proficiency in using Neo4J, OrientDB, AllegroGraph, JanusDB, etc.
- Additional advantage with proficiency in Natural Language Processing
- Additional advantage with proficiency in using Keras, TensorFlow, Caffe, Torch/PyTorch, Spark MLlib, or any other Deep Learning framework
- Track record in leading data science projects and delivering from end to end.
Interested candidate, please submit your updated resume in MS WORD format to: firstname.lastname@example.org
We regret that only shortlisted candidates will be notified.
Name: Yong Whei Jie
Registration Number: R1110096
EA Licence Number: 02C3423
Octavius, Whei Jie Yong EA License No.: 02C3423 Personnel Registration No.: R1110096