Data Scientist II-2
Core
Develops machine learning and deep learning models for financial applications like transaction classification, risk modeling, and temporal analysis to improve financial health and decisioning.
Role type
Mid-level machine learning engineer (financial services)
Builds
Production ML models for transaction classification, risk modeling, and intelligent decisioning
Domain
Financial services / Payments / Open Banking
Deliverable
production ML models
Required skills
Machine learning model development, Deep learning (LSTM, RNN, Transformer), Statistical modeling, NLP, SQL, Python, Data visualization
Preferred skills
Financial transactional data experience, Risk evaluation, Credit risk modeling, Kubernetes, Docker, REST APIs, Event Streams, TensorFlow, Scikit-learn, Pandas
Technologies
TensorFlow, Python, Scikit-learn, Pandas, XGBoost, LightGBM, CATBoost, SVM, Random Forest, LDA, OLS, Multinomial logistic regression, LSTM, RNN, Transformer, Kubernetes, Docker, REST APIs, Event Streams
Responsibilities
Manipulate large datasets to draw insights using statistical and technical analytical techniques; Design and implement ML models for financial applications; Measure, validate, monitor, and improve performance of internal and external ML models; Propose creative solutions to new challenges; Present technical findings to business leaders and clients; Develop scalable solutions using best practices in ML and data science.
Seniority
Mid-level, hands-on IC
