Connecting people across the world is a complex problem with many machine-learning applications. The purpose of this role is to implement models and algorithms to solve complex business problems in risk & fraud domains. Successful outcomes will significantly impact our hundreds of millions of daily active users around the globe.
Responsibilities:
Work with management and partner teams to design and implement solutions for given objectives.
Commitment to success metrics, ensuring low FP, and accurately measuring the impact and model performance.
Lead technical efforts to improve the performance of our Risk & Fraud models and propose initiatives in that domain to shape our long-term risk-mitigation vision.
Autonomously find solutions to complex data problems and understand the data generation process and the challenges with the data.
Leverage the extensive data received from our application to enhance model performance and accuracy.
Requirements
BSc in the field of engineering, math, statistics, etc.
Minimum of 2 years of experience in designing, developing and deploying production-level risk & fraud-related solutions with a proven business impact.
Worked in a team with peer review processes.
Fluency in Python and SQL.
Strong communication skills. Ability to present technical subjects to non-technical stakeholders.
Advantages:
Knowledge in statistics: Statistical tests, Bayesian inference, MCMC, Likelihood estimators.
Led the efforts with a proven impact to mitigate Spam, Risk and Fraud at scale.
Strong passion for machine learning and investing independent time towards learning, researching and experimenting with new innovations in the field.
Experience working in AWS, NodeJS lambda functions, DataDog, and operational experience.
