Senior Applied Scientist, FinAuto
Core
Build and deploy advanced algorithmic systems using machine learning and statistical techniques to identify and prevent theft, fraud, abuse, and waste (TFAW) in financial transactions, optimizing millions of daily transactions.
Role type
Senior Applied Scientist (FinAuto)
Builds
Production ML models for fraud detection and financial transaction optimization
Domain
FinTech / Financial Services / Machine Learning
Deliverable
production ML models
Required skills
Machine learning, statistical techniques, neural deep learning methods, data mining, Java, C++, Python
Preferred skills
R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Hadoop, large scale distributed systems
Technologies
Java, C++, Python, R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Hadoop, Spark
Responsibilities
Design, develop, evaluate, and deploy scalable ML models for predictive learning; Analyze large historical business data to automate and optimize processes; Collaborate with engineering teams for real-time model implementation; Mentor scientists and engineers in ML techniques; Establish automated processes for model development and validation.
Seniority
Senior, hands-on IC with mentorship
