# Raghuram Selvaraj

> Software Engineer

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

Software and machine learning engineer with 5+ years of experience working in AdTech and FinTech. Foundational understanding of advertising, observability, data infrastructure, global capital markets, and buy-side firms. Skills: AI/Machine Learning, scikit-learn, Keras, Python, NumPy, Pandas, boto3, SQL, AWS, Java, C, Matlab, TypeScript, and React.js. Bachelor of Science in Computer Engineering at Purdue University.

## Work Experience
### Software Dev Engineer 1 @ Amazon
Jan 2022 – Jan 2025 | New York, United States

### Software Engineer 1 @ Charles Schwab
Jan 2021 – Jan 2022 | Austin, Texas, United States

### Software Engineer - Risk Technology (FIC) @ Millennium
Jan 2020 – Jan 2020 | New York, United States
♦ Developed UI to provide risk managers the ability to visualize time series of credit risk exposures to better understand the efficacy of risk model with respect to its VaR metrics due to unexpected behavior after COVID. Technologies: Python, Streamlit, Pandas
♦ Built a reporting tool on Redshift that allowed the Risk managers to easily review log files from the model for a specific portfolio to confirm there were no errors or warnings. Technologies: Redshift, Python, Streamlit
♦ Cost-optimized use of Redshift by maintaining CDS Index net exposures and positions in S3 for UI queries. Technologies: Redshift, S3, boto3
♦ Developed framework to dynamically detect and visualize missing data and significant spikes in time series used in firm’s risk modeling workflow, and generated summary statistics for each series. Technologies: Python, Pandas, NumPy

### Machine Learning Engineer @ Pleeco
Jan 2019 – Jan 2019 | New York, United States
♦ Developed new AI application that uses reinforcement learning to easily upload and classify new datasets interactively ranging in size from 10 GB – 100 GB and provided initial results to user in under one minute. Technologies: Python, Keras, Pandas
♦ Built a Python framework to allow engineers to leverage Gym to quickly validate the outcome of their neural network model by running 1000 iterations of simulations in a test environment. Technologies: Python, Gym, Keras.
♦ Designed a Jupyter notebook to provide transparency to each stage of the simulations executed in Gym that can plug and play with any of the company’s deep learning models, including Keras, PyTorch.

### Machine Learning Engineer @ Pleeco
Jan 2018 – Jan 2018 | New York, United States
♦ Developed RESTful Python microservice for a financial analysis dashboard that displayed market data and volatility for a Ticker. Technologies: Python, Docker, Vagrant CentOS VM, and Ansible 
♦ Cut reconciliation time to 5 minutes from 1 day by replacing a Java application that used a line-by-line reconciliation that did not scale with a Python script leveraging Pandas. Technologies: Python, Pandas, cx_Oracle, xlsxreader
♦ Benchmarked 8 machine learning algorithms to determine which one performed the best on a representative data set from the firm’s production portfolio analysis suite which the firm used to select the best algorithm for their core product. Outcome:  SVM most accurate but didn’t scale due to number of features required.  Naïve Bayes performs well, CPU/Memory intensive due to text-to-numeric conversions. Neural Net requires a lot of configuration and might be more complex than needed. Technologies: Decision Tree, Naïve Bayes, SVM, Random Forest, Gradient-Boosted Tree, K-Means Analysis, Neural Network, KNIME


## Education
### Bachelor of Science - BS in Computer Engineering
Purdue University

### Sparta High School


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

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Source: https://flows.cv/raghuram
JSON Resume: https://flows.cv/raghuram/resume.json
Last updated: 2026-04-18