IDT Corporation
Technology DW
SeniorDataScientist
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Scientist at IDT Corporation. Skills: Machine Learning, MLOps, Data Science, Modeling. Design machine learning models. Develop machine learning models”
What You'll Achieve.
Increase accuracy; Increase recall; Increase precision
Industry & Context.
Data-driven decision making
What They're Looking For.
Must Have
5+ years of professional experience in Data Science, Bachelor’s degree in a quantitative field, Advanced use of Pandas, Advanced use of Numpy, Advanced use of PyTorch/TensorFlow, Advanced use of Scikit-learn, Proficiency in SQL
Nice to Have
PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
Design machine learning models
Develop machine learning models
Maintain machine learning models
Build models to predict bad actors
Develop supervised models
Develop unsupervised models
Design generative models
Deploy models into product
Increase model accuracy
Increase model recall
Increase model precision
Lead statistical design of A/B testing
How You'll Work.
Team & Collaboration
MLOps functions
Full Job Description
## Description 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. ## 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. ## 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
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