# Anusha Nerella - Episode 77

Page: https://stenobird.com/podcast/acm-bytecast-547158/anusha-nerella-episode-77
Text version: https://stenobird.com/podcast/acm-bytecast-547158/anusha-nerella-episode-77.md
Podcast: [ACM ByteCast](https://stenobird.com/podcast/acm-bytecast-547158)
Published: 2025-11-10T16:54:16+00:00
Episode link: https://acmbytecast.podbean.com/e/anusha-nerella-episode-77/
Audio file: https://mcdn.podbean.com/mf/web/yd9ziebhxy6habcy/ACM_Bytecast_-_Episode_77_-_Anusha_Nerella_-_Mix9yiz2.mp3
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JSON: https://stenobird.com/v1/public/podcasts/acm-bytecast-547158/episodes/anusha-nerella-episode-77
Duration seconds: 2629

## Resource

In this episode of ACM ByteCast, Rashmi Mohan hosts Anusha Nerella, a Senior Software Engineer at State Street. She has more than 13 years of experience working on building scalable systems using AI/ML in the domain of high-frequency trading systems and is passionate about driving adoption of automation in the FinTech industry. Anusha is a member of the ACM Practitioner Board, the Forbes Technology Council, and is an IEEE Senior Member and Chair of IEEE Women in Engineering Philadelphia chapter. She has served as a judge in hackathons and devotes significant time mentoring students and professionals on the use of AI technologies, building enterprise-grade software, and all things FinTech.Anusha traces her journey from growing up with limited access to technology to teaching herself programming to working at global firms including Barclays and Citibank and leading enterprise-scale AI initiatives. Anusha and Rashmi discuss the challenges of applying AI to a field where money and personal data are at stake, and workflows that prioritize trust, security, and compliance. They touch on the importance of clear data lineage, model interpretability, and auditability. The discussion also covers observability, tooling, and the use of LLMs in finance. Along the way, Anusha shares her personal philosophy when it comes to building systems where speed and reliability can be competing priorities.

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## Transcript

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