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Skills
Apache Sparkunmatched
Artificial Intelligence (AI)unmatched
Automationunmatched
Banking Servicesunmatched
Business Processesunmatched
Business Skillsunmatched
Business Supportunmatched
Cloud Computingunmatched
Communication Skillsunmatched
Continuous Deployment/Deliveryunmatched
Continuous Integrationunmatched
Data Analysisunmatched
Data Scienceunmatched
Distributed Computingunmatched
Enterprise Applicationsunmatched
Financial Servicesunmatched
Forecastingunmatched
Machine Learningunmatched
Microsoft Windows Azureunmatched
Natural Language Processing (NLP)unmatched
Predictive Modelingunmatched
Production Machiningunmatched
Python Programming/Scripting Languageunmatched
Quantitative Analysisunmatched
Riskunmatched
Risk Analysisunmatched
Risk Managementunmatched
Risk Modelingunmatched
SQL (Structured Query Language)unmatched
Scalable System Developmentunmatched
Description
This role will focus on developing production-grade AI, machine learning, and analytics platforms that support critical business functions including risk management, fraud detection, compliance, customer intelligence, and operational optimization. The ideal candidate combines deep technical expertise with the ability to drive business outcomes through data-driven innovation.
What You'll Tackle:
Design and deploy enterprise AI and machine learning solutions.
Build scalable analytics pipelines using distributed computing frameworks.
Develop predictive models, forecasting solutions, and advanced analytics capabilities.
Implement MLOps frameworks and automated model deployment pipelines.
Partner with engineering teams to integrate models into enterprise applications.
Lead model monitoring, governance, validation, and explainability initiatives.
Drive AI adoption across business processes and decision workflows.
Collaborate with technology, risk, compliance, and business stakeholders.
QUALIFICATIONS
10+ years of experience in data science, machine learning, AI engineering, or quantitative analytics.
Advanced expertise in Python and SQL.
Strong experience with Databricks and Apache Spark.
Experience with Azure ML and cloud-based analytics platforms.
Hands-on expertise with TensorFlow, PyTorch, scikit-learn, XGBoost, and MLflow.