Machine Learning Engineer

Job Classification:

Prudential’s Global Technology team is the spark that ignites the power of Prudential for our customers and employees worldwide. Our organization plays a critical and highly visible role in delivering customer-driven solutions across every area of the company. The Global Technology team is made up of diverse, agile-thinking, and highly skilled professionals; we use our combined capabilities to enable the organization with innovation, speed, agility, scalability and efficiency.

The Global Technology team takes great pride in our culture where digital transformation is built into our DNA. When you join the Global Technology organization at Prudential, you’ll unlock a challenging and impactful career – all while growing your skills and advancing your profession at one of the world’s leading financial services institutions.

Data Tech team at Prudential Financial is looking for a ML Engineer to join a diverse team dedicated to providing best-in-class data services to our customers, stakeholders, and partners.

As a part of our CDO organization, you will work with our Data Science and BUs to define solutions for operationalizing data-driven decision making in a cost effective and scalable manner. A full stack engineer with deep understanding of data science and software engineering practices.

Responsibilities:

• Strong computer science fundamentals such as algorithms, data structures, multithreading, object-oriented development, distributed applications, client-server architecture.
• Design and implement Machine learning models and data ingestion pipelines.
• Develop and support a platform that enables data scientists to rapidly develop, train, and experiment with machine learning models.
• Expand and optimize data pipelines, data flow, and collection for cross functional teams.
• Create and maintain optimal data pipeline architecture by assembling large, complex data sets to meet functional and non-functional business requirements.
• Identify and implement internal process improvements including automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
• Support the building of machine learning, data platforms, and infrastructure required for optimal data extraction, transformations, and loading of data from a wide variety of data sources.
• Work with architecture, data, and design teams to assist with data related technical issues and support data infrastructure needs.
• Implement Machine Learning (ML) and Big Data platforms in Hybrid and multi-cloud environment specifically in AWS SageMaker environment
• Experience in container, streaming and messaging technologies is a plus

Skills / Qualifications:

• Bachelor's degree in computer science, data science, mathematics, or a related field. Master’s degree preferred
• At least two years' experience as a machine learning engineer.
• Advanced proficiency with Python framework, Java and Scala
• Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
• Good understanding of mathematics, statistics, and algorithms.
• Excellent analytical and problem-solving abilities.
• Great communication and collaboration skills.