Risk Process Analyst - Market Behavior Analytics

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.

One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We're devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

The Risk Process Analyst is responsible for supporting the development and execution of capabilities that include models, analytical tools, and tests used for risk management. Key responsibilities include obtaining an understanding of Bank-wide processes, including their risks, underlying data, and process steps, and using that knowledge to build capabilities for the Front Line Units/Control Functions to better manage their risk and operational effectiveness. This role supports other risk analysts and managers to complete a set of task aligned to risk and data management.

Job Description Summary

Bank of America's Global Risk Management business is looking for a Risk Process Analyst in the Market Behavior Analytics group within Global Risk Analytics. This group is responsible for developing surveillances and other sophisticated controls over activities in our Global Markets business. These controls detect potentially suspicious activities and patterns of behavior. Building these controls requires knowledge of big data techniques, ability to architect systems that can efficiently scale to hundreds of billions of data points per day, machine learning over unstructured and structured data, graph analytics, and experience with building UI for data rich applications.

Key responsibilities include:

• Understanding financial data: schemas, flow, size, data issues, data controls, etc.
• Building performant big data pipelines that are the backbone of building large scale surveillance systems.
• Building surveillance models using sophisticated modeling techniques including machine learning and AI.
• Testing the efficacy of surveillances using advanced modeling techniques.

• Successful candidates will have a Bachelor's or Master's degree in computer science or related disciplines.
• Ability to analyze and find interesting patterns in data with at least one of the following:
• Implement distributed algorithms on large amounts of data using Big Data, batch and streaming technologies like Hadoop, Spark, Flink, Kafka etc.
• Build user facing UI applications over large amounts of data using technologies like React, Angular, JavaScript etc.
• Knowledge and working experience with SQL and NoSQL databases such as MongoDB, HBase, Cassandra, Oracle etc. to process large scale data.
• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences
• Ability to effectively present findings, data, and conclusions to members of the team and management.
• Ability to operate independently with guidance to deliver sub tasks and the ability to participate in group settings.
• 0-2 years of relevant experience in software engineering in Quantitative Finance or other industries.

• Knowledge and experience in machine learning / AI models
• Knowledge and experience with financial data sets
• Ability to code proficiently in at least one programming language like Python or Java.
• Proficiency in SQL and in at least one NoSQL data store.