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Future Ready Careers: CS + Finance with Bank of America
Computer science careers involve something called computational thinking, and computational thinking skills parallel the skills necessary to be successful in the finance industry. Hear from three women in leadership roles at Bank of America as they talk about the interwoven skills of computer science and finance. Originally aired on May 10, 2022.
Pathways in CS+Finance
Some roles in CS+ Finance are accessible with an Associate’s Degree or certificate. These include roles in IT Support, Network Administration, user design of human-facing systems (UX), and possibly Software Development. Other roles may require a Bachelor’s Degree, while research scientist roles may require a Master’s or Ph.D. The following subfields of CS are ideal for those eyeing a career in finance:
Computational Finance: This applied subfield of CS focuses on the application of computer algorithms to financial problems. It covers topics such as financial modeling, risk management, and algorithmic trading.
Data Science: In the financial sector, data science is used to identify trends, predict market movements, and inform investment strategies. Techniques like machine learning and statistical analysis help in risk assessment, fraud detection, and customer segmentation.
Information Security: Information security is crucial in finance for protecting sensitive financial data and ensuring compliance with regulations. This work involves implementing strong cybersecurity measures, including cryptography and network security, to safeguard against data breaches and cyber attacks.
Software Engineering: Software engineers in finance develop and maintain programs for trading, banking transactions, and portfolio management. They ensure these systems are efficient, scalable, and secure.
Artificial Intelligence (AI): AI in finance is used to automate trading, personalize financial services, and improve decision-making through predictive analytics. Technologies like natural language processing are employed in customer service, while machine learning algorithms are used for credit scoring and algorithmic trading.
Computer Networks: Computer networks in finance support the connectivity and communication essential for executing financial transactions and sharing information globally. Network security and architecture are key foci, ensuring reliable and secure data transmission across various financial institutions.
