What does it take to protect and maintain the most sensitive data for over 220 million people and 25 million businesses? What does it take to meet daunting challenges and shape solutions that pioneer industries and improve lives? At Experian, we are the trusted power behind data and the leading global information services company, providing everything from fraud and identity protection, to data analytics and credit scores. Our products help decision-making for consumers and businesses alike.
With operations stretching globally, Experian is 17,000 people strong, supporting clients and operations in more than 80 countries. Generating nearly $5 billion in revenue annually, Experian is primed for growth and searching for the most talented and innovative people to join our family and take us to new heights.
Experian's Consumer Services (ECS) group is defining the next Big Data thing for consumers.
What could be more exciting - personally and professionally - than being part of a disruptive business? Consider starting your career with the industry's best by joining the Leader that continues to disrupt the competition. As the market leader, we pride ourselves on building new markets and leading the pack through continuous evolution and innovation. It's a position ECS has enjoyed for more than a decade and we aren't looking to stop now.
Experian's Technology team is seeking a talented Solutions Architect. The Enterprise Architecture team at ECS is creating a unified enterprise Machine Learning (ML) Platform that will enable end to end solution for other business lines to build and deploy their ML models. This Solutions Architect role will focus on building a unified solution to automate ML and Natural Language Processing (NLP) projects. The system will encompass not just the model learning itself, but also many practical challenges in ML systems: feature extraction/feature definition, data validation, monitoring, and management of features/models.
* Design and develop a framework for easily assembling training workflows and data pipelines for machine learning.
* Design and develop tools that allow large teams of modeling engineers to iterate on model quality and that help them keep their ML systems running smoothly.
* Bachelor's degree from an accredited four-year university required, preferably in Computer Science, Engineering or similar field.
* Expertise with big data computation frameworks (Hadoop, Spark, etc).
* Solid grounding in statistics, probability theory, data modeling, machine learning algorithms, and software development techniques and languages used to implement analytics solutions.
* Experience with large-scale production machine learning preferred.
* Experience in neural networks/deep-learning techniques preferred.
* Experience with cloud services (AWS, Azure, Google) is a plus.
* Experience using machine learnin toolkits (scikit-learn, Tensorflow, Jupyter, etc) required.