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Machine Learning Researcher

GCash Quiapo District, Philippines
Posted over 1 year ago Permanent Competitive

Machine Learning Researcher

GCash Quiapo District, Philippines
Machine Learning Researcher
Do you want to take the first step in making Filipinos' lives better everyday? Here in GCash we want to stay at the forefront of the FinTech industry by creating innovative, meaningful, and convenient financial solutions for the nation! G ka ba? Join the G Nation today!

ROLES AND RESPONSIBILITIES
  • Research and develop machine learning models tackling problem domains such as credit scoring, personalization, fraud detection, entity resolution, etc.
  • Discover new applications of machine learning and AI to solve emerging business needs
  • Collaborate with data strategists and machine learning engineers to deliver end-to-end AI solutions to business teams
  • Publish and share research internally within the Advanced Analytics team and to the broader business teams

QUALIFICATIONS
  • 2+ years experience in an equivalent or functionally similar data role.
  • An undergraduate degree preferably in Statistics, Computer Science, Physical Science, Economics, or a related technical field. A graduate degree is a plus.
  • A strong and demonstrable understanding of SQL and Python or R for advanced analysis.
  • A strong and demonstrable understanding of machine learning with big data. Expertise in one or more areas among recommender systems, forecasting, NLP, network science, and reinforcement learning is a big plus.
  • Familiarity with data cloud services surrounding analytical and automation functions.
  • Familiarity with version control software such as git.
  • A talent for research and the presentation of interpretable insight.

What We Offer

Opportunity for career growth and development in the #1 FinTech company in the country Working with a dynamic and highly collaborative team who want to change the game A company that values their people with highly competitive and flexible compensation and benefits package
Job ID  R0000013198
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