Machine Learning Engineer

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

This is a hands-on role for machine learning and analytics related data-engineering, operations, automation and application development. It involves building applications and analytics pipelines for business using machine learning, statistical methods and other analytics techniques.

Responsibilities:

• Build modelling pipelines, data science related applications and model life-cycle management systems using machine learning, statistical methods and other analytics techniques.
• Build analytics solutions for consumer bank, including core banking, cards and wealth management businesses.
• Plan and build data-driven banking ecosystem, including models for customer experience and marketing.
• Monitor and control all phases of development process and analysis, design, construction, testing, and implementation as well as provide user and operational support on applications to business users
• Ensure essential procedures are followed and help define operating standards and processes
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

• Qualifications:

• 3+ years of experience in building solutions with machine learning, including data preparation, scoring pipelines and analytics techniques.
• In depth knowledge of building data processing pipelines, scalable model deployment and model evaluation and monitoring.
• Working knowledge of model performance monitoring, feature engineering and modelling pipeline automation.
• Good understanding of the principles of software engineering and data analytics.
• Hands-on experience with XGBoost, scikit-learn, PySpark, Tensorflow is preferred.
• Experience in consumer banking or other financial services domains is preferred.

Education:

• Bachelor’s degree/University degree or equivalent experience