# Krisha Gala

> Software Engineer @ Current

Location: New York, New York, United States
Profile: https://flows.cv/krisha

As a Software Engineer at SoFi, I built and developed various features and solutions that enhanced the user experience and improved the efficiency of the transactions reissue automation system. For example, I designed and developed a self-serve UI that removed engineering bottlenecks from the loop and saved over 90% of the time for engineers and our internal customers. I also created APIs to render check details and email configurations in ~30 transaction data pipelines and streamlined the team’s on-call process using Datadog, Rollbar, and OpsGenie, improving incident remediation by 50%.

Before joining SoFi, I completed my Master of Science in Computer Science from Arizona State University, where I gained hands-on experience in software, machine learning, and data science domains. I worked on several projects that involved mapping Covid-19 spatial data using PostGIS, designing a localization algorithm for efficient spatial data scraping, developing software to create 2D maps and a centralized infrastructure using Mapbox, Leaflet, Javascript, and Python, and utilizing topic modeling to model time series data on Covid 19 controversies. I also mined 5 million healthcare insurance data sources to build a cost-optimized prescription drugs system, transforming raw data to extract meaningful prescription and provider information for detailed analysis.

I am a quick learner and problem solver, with a proven track record of adapting to new technologies and effectively applying them in my work. I am confident in my ability to deliver practical solutions that can benefit any team. I am excited about exploring new opportunities and contributing my skills to further the success of any organization.

## Work Experience
### Software Engineer @ Current
Jan 2024 – Present | New York, United States

### Software Engineer @ SoFi
Jan 2023 – Jan 2024 | United States
- Built APIs for transactions reissue automation to reduce engineering time spent by ~6 hrs/week and errors by 100%.
- Designed and developed a self-serve UI for returns and reissue automation, removing engineering bottleneck from the loop, and saving over 90% of time for engineers and our internal customers.
- Created APIs to render check details and email configurations in ~30 transaction data pipelines.
- Streamlined team’s oncall process using Datadog, Rollbar, and OpsGenie, improving incident remediation by 50%.

### Software Developer @ Arizona State University (Knowledge Enterprise)
Jan 2022 – Jan 2023 | Arizona, United States
- Mapped Covid 19 spatial data using PostGIS to create data pipeline for health vulnerability detection based on geographical and community patterns from over 100000 data points.
- Designed a localization algorithm for efficient spatial data scraping, enabling accurate extraction and analysis of geospatial information from various sources.
- Developed software to create 2D maps and a centralized infrastructure using Mapbox, Leaflet, Javascript, and Python.
- Utilized topic modeling to model time series data on Covid 19 controversies, collaborating with Sandia National Lab.

### Data Scientist @ W. P. Carey School of Business – Arizona State University
Jan 2022 – Jan 2023 | Arizona, United States
- Mined 5 mil healthcare insurance data sources to build a cost-optimized prescription drugs system.
- Transformed raw data to extract meaningful prescription and provider information for detailed analysis.
- Created a distributed SQL query infrastructure for efficient performance in over 300 mil data points.

### Graduate Research Assistant @ Ira A. Fulton Schools of Engineering at Arizona State University
Jan 2021 – Jan 2022 | Arizona, United States
- Analyzed and identified the intention of 135000 git commits for creating a code vulnerability finder model.
- Annotated over 45000 commits by 816 authors and 5 mailing lists with 400000 messages to create a database.
- Achieved 54% precision in identifying malicious commits and 62% for commits that patch vulnerabilities.

### Research Intern @ KJ Somaiya College of Engineering, Vidyavihar
Jan 2019 – Jan 2019 | India
- Programmed a Python code to extract 2200 real-time tweets from Twitter and visualized it.
- Processed the collected data and performed sentiment analysis to find 26% positivity and 21% negativity in tweets.


## Education
### Master of Science - MS in Computer Science
Arizona State University

### Bachelor of Technology - BTech
KJ Somaiya College of Engineering, Vidyavihar


## Contact & Social
- LinkedIn: https://linkedin.com/in/krisha-gala

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Source: https://flows.cv/krisha
JSON Resume: https://flows.cv/krisha/resume.json
Last updated: 2026-04-05