Senior Data Scientist
We are looking for a Senior highly technical Data Scientist to join our established Analytics department. This is a modeling-heavy role focused on building high-performance, reproducible machine learning systems that drive core business decisions. You will join the newly formed AI Lab which is entrusted with growing our AI/ML capabilities at IDT.
We are looking for a veteran modeling expert who thrives on building novel ML architectures from the ground up for business functions like fraud detection, customer engagement, process performance and finance.
We are looking for a veteran modeling expert who thrives on building novel ML architectures from the ground up for business functions like fraud detection, customer engagement, process performance and finance.
Responsibilities:
Advanced ML R&D: Design, develop, and maintain cutting-edge, custom machine learning models for production environments.
Behavioral Forecasting: Build advanced models to predict bad actors in our transaction flow.
End-to-End Modeling: Develop and implement both supervised and unsupervised models from scratch to find anomalies and next likely outcome.
Content Generation: Design generative models based on profile and transaction data.
Production Deployment: Deploy models into product in a real-time environment.
Interact with MLOps functions to maintain models and increase accuracy, recall and precision.
Experimental Design: Lead the statistical design and analysis of A/B testing to validate model performance and business hypotheses.
Behavioral Forecasting: Build advanced models to predict bad actors in our transaction flow.
End-to-End Modeling: Develop and implement both supervised and unsupervised models from scratch to find anomalies and next likely outcome.
Content Generation: Design generative models based on profile and transaction data.
Production Deployment: Deploy models into product in a real-time environment.
Interact with MLOps functions to maintain models and increase accuracy, recall and precision.
Experimental Design: Lead the statistical design and analysis of A/B testing to validate model performance and business hypotheses.
Requirements:
Experience: 5+ years of professional experience in Data Science, with a strong portfolio of building and shipping original ML models.
Deep theoretical and practical understanding of supervised/unsupervised learning, including Boosting, NN, Bayesian, Clustering, and related frameworks.
Core Stack:
Python: Advanced use of Pandas, Numpy, PyTorch/TensorFlow, and Scikit-learn for complex feature engineering, custom model design, and pipeline optimization.
SQL: Proficiency in querying and structuring data from large-scale databases.
MLOps: Experience using MLOps tools like MLflow or ClearML in model development and inference.
Education: Bachelor’s degree in a quantitative field (Computer Science, Statistics, Mathematics, or related).
Deep theoretical and practical understanding of supervised/unsupervised learning, including Boosting, NN, Bayesian, Clustering, and related frameworks.
Core Stack:
Python: Advanced use of Pandas, Numpy, PyTorch/TensorFlow, and Scikit-learn for complex feature engineering, custom model design, and pipeline optimization.
SQL: Proficiency in querying and structuring data from large-scale databases.
MLOps: Experience using MLOps tools like MLflow or ClearML in model development and inference.
Education: Bachelor’s degree in a quantitative field (Computer Science, Statistics, Mathematics, or related).