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M-DAQ Global

Data Scientist

Department
Engineering
Job Type / Location
onsite
Experience Required
1+ years
Posted On

About M-DAQ Pte. Ltd.

M-DAQ builds over-the-top (OTT) applications to facilitate cross-border business for various industries. These include securities markets, e-Commerce platforms and payment solutions providers. M-DAQ achieves this through our proprietary technology, together with the remittance license awarded by the Monetary Authority of Singapore. M-DAQ was awarded “Best Tech Company To Work For 2019” by Singapore Computer Society (SCS).

M-DAQ is a high-growth FinTech start-up that focuses on proprietary best-in-class corporate FX solutions across Asia. We have to date processed over $10 billion in FX transactions and generated hundreds of millions of dollars in revenue for our partners and savings for their end-customers. Having recently concluded our Series D financing round, we have exciting plans to leverage our FX expertise in even more verticals.

Why Us?

  • Have a positive impact to the world’s economy by creating a World without Currency BordersTM
  • Team Innovation Mindset, People-Oriented
  • Challenging environment, offering great opportunities to learn and grow
  • Creative and Innovative Workplace

Key Responsibilities

  • Work with data engineers and product managers to build, deploy and scale data science solutions on M-DAQ products, such as time series prediction, optimization, credit scoring, fraud detection, etc.
  • Work on model tuning and bringing model to production. Monitor the performance, improve, and refine accordingly.
  • Work with product managers and business team to identify new opportunities in monetizing data science solutions.

Desired Skill Set and Attributes

  • Degree in Computer Science, Electrical/Computer Engineering, Mathematics/Statistics, or related technical disciplines.
  • 1 - 4 years working experience in data science and data analytics or relevant field.
  • Proficient in one or more of the following programming languages: Python, R, C++, Java, Scala.
  • Strong working knowledge of machine learning principles including time series prediction, Natural language processing, classification, clustering.
  • Experience in ETL, feature engineering, hyperparameter tuning and model selection
  • Experience in bringing models from development to production in AWS or GCP
  • Experience in Deep Learning framework such as pyTorch, Keras is a plus
  • Experience in credit scoring is a plus
  • Ability to recognize business needs and communicate with multiple stakeholders

View Assessment Process

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