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Digital Brain Interface
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Veom Nemade

  • LinkedIn

Software Engineer

Website: www.veomn.com

Phone: 469-750-7649

Email: vnn210000@utdallas.edu

Address: Dallas, Texas

Github: github.com/254176

LinkedIn:  linkedin.com/in/veomn

A Bit About Me

I’m a software engineer passionate about using data science and machine learning to solve problems in genomics, healthcare, and biological systems. Currently exploring projects in bioinformatics and preparing for graduate research in computational biology.

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2022 -2026

B.S in Software Engineering

University of Texas at Dallas                                                            Major Core GPA 3.6

Relevant Coursework

Data Science Certification, Neuro-Net Math Certification,  OOP, Algorithms, Data Structures, Machine Learning, Full Stack Development, Networking (Socket Programming), Data Science, Bioinformatics

Work Experience

Jan 2025 -Aug 2025

Rove

Data Science and Machine Learning Intern

  • Built a multi-sheet financial analytics model (GMV, take rate, redemption cost, partner payouts) to quantify unit economics and identify high margin vs. loss-making scenarios.

  • Analyzed partner and redemption datasets to compute revenue/cost per mile and produced data-driven insights that guided pricing and strategy decisions.

  • Designed scenario-analysis tools and dashboards that modeled how changes in redemption rate, partner pricing, and take rate impact profitability and overall business performance.

Technical Skills: Excel financial modeling (GMV, take rate, unit economics), revenue/cost analysis, partner-pricing modeling, scenario forecasting, dashboard creation.

Jan 2024 - Aug 2024

UTD Nebula Lab

API & Platform Team Member

  • Participated in Agile practices including daily stand-ups, sprint planning, and peer code reviews to drive project success.

  • Automated extraction and transformation of UTD course data using web scraping, structuring data with an optimized MongoDB schema for efficient querying.

  • Developed Go-based RESTful APIs with features like advanced filtering, caching, and secure authentication, enhancing API performance and security.

Technical Skills: Go APIs, MongoDB, React.js, JSON, Agile Scrum

Skill Summary 

Technical Skill Summary

  • Programming Languages: Python, Go, Java, JavaScript, C, C++

  • Data Science / Machine Learning: Pandas, NumPy, Scikit-Learn, TensorFlow, XGBoost, Biopython, PCA & clustering, Statistical Modeling

  • Bioinformatics: BLAST parsing, DNA/FASTA processing, GC/ORF/codon-usage analysis, Gene-expression matrix analysis, Sequence alignment metrics

  • Visualization: Matplotlib, Seaborn, Plotly, Heatmaps, PCA plots, Clustering visualizations

  • Tools: Git, Jupyter, VS Code, AWS, Google Cloud

  •  Web Development: React, Go APIs, Node.js, Express.js, PHP, HTML, CSS

  • DevOps & Cloud: Docker, AWS, Google Cloud, CI/CD fundamentals

  • Databases: MongoDB, MySQL

  • System Design: RESTful API development, Microservices architecture, ETL pipelines, Data-pipeline engineering

  • Financial Analytics: Excel financial modeling (GMV, take rate, unit economics), revenue/cost analysis, partner-pricing modeling, scenario forecasting, profitability dashboards

  • AWS Tools: Glue, Redshift, Athena, S3 Bucket

Soft Skills

​Effective communication, critical thinking, problem-solving, collaboration and teamwork.

Certifications

  • Data Science Certification - UTD

  • Neuro-Net Math - UTD

  • AWS Certified Cloud Practitioner

  • Google Cybersecurity – Coursera 

  • JavaScript Algorithms and Data Structures – FreeCodeCamp

  • Machine Learning with Python – FreeCodeCamp 

  • Fullstack GoLang React: Design to Reality – Udemy 

  • AWS Data Engineer Certification - In Progress

Campus Involvement

  • Bioinformatics Specialization – UC SanDiego University (Coursera)

  • Genomic Data Science Specialization – Johns Hopkins University (Coursera)

Campus Involvement

  • Hack UTD - Developed solutions for real-world challenges in a collaborative hackathon setting.​

  • UTD Nebula Labs - Contributed technical expertise and innovative ideas in software projects.

Projects

Real-Time Customer Behavior Analytics Pipeline (AWS)

  • Built a real-time analytics pipeline using Kinesis, Lambda, Glue ETL/DQ, Redshift, and QuickSight, reducing event-to-dashboard latency to under 2 minutes.

  • Developed PySpark ETL workflows for cleaning, transforming, and partitioning large-scale event data with automated schema inference.

  • Optimized Redshift performance and resolved a $1.3k cost spike, implementing AWS Budgets and cost-control policies.

  • Delivered a fault-tolerant streaming architecture and interactive QuickSight dashboards for customer behavior, anomalies, and engagement trends.

Churn Guard

Github

  • Built a predictive analytics platform using Python and Scikit-Learn to identify customer churn, achieving an accuracy improvement of 15% through data preprocessing and model tuning.

  • Analyzed large datasets to derive actionable insights for client retention strategies.

AI-Powered Retrieval-Augmented Generation (RAG) System

Github

  • Built a Retrieval-Augmented Generation (RAG) system using Microsoft GraphRAG andAutoGen agents with local models from Ollama for offline embedding and inference.

  • Enabled function calling with non-OpenAI LLMs via a Lite-LLM proxy, supporting free and offline model use.

  • Developed an interactive user interface with Chainlit for seamless, multi-threaded conversations.

  • Integrated Mistral AI and Nomic embeddings to improve knowledge search and retrieval.

BLAST Result Parser (Bioinformatics Tool)

Github

  • Developed a Python-based BLAST Result Parser to automate alignment analysis across XML and tabular formats, reducing manual filtering time by >80%.

  • Implemented chainable filters (e-value, identity %, bit score) and standardized alignment fields using Biopython and pandas.

  • Built summary-statistics and top-hit extraction modules to support downstream genomic workflows.

  • Enabled multi-format export (CSV/JSON/DataFrame) to integrate alignment results into computational pipelines.

DNA Analysis Toolkit (Comprehensive Sequence Analysis)

Github

  • Built an end-to-end DNA analysis toolkit performing GC-content profiling, ORF detection, codon-usage analysis, translation, and restriction-site mapping.

  • Designed memory-efficient batch processing for large FASTA datasets (1000+ sequences).

  • Created publication-quality visualizations (ORF maps, GC-content plots, codon-usage heatmaps) using Matplotlib/Seaborn.

  • Applied Biopython workflows to generate molecular properties (molecular weight, Tm) for cloning and primer-design applications.

Gene Expression Visualizer (RNA-seq & Microarray Analysis)

Github

  • Developed a gene-expression visualization tool that automates PCA, hierarchical clustering, correlation matrices, and QC plots for RNA-seq/microarray datasets.

  • Designed a unified API enabling complete exploratory analysis with a single command (“generate_report”).

  • Implemented dimensionality reduction (PCA) and clustering pipelines to identify co-expression patterns and sample relationships.

  • Improved accessibility for biologists by eliminating hundreds of lines of manual plotting code across multiple libraries.

VeomShopping.com

Github

  • Created a full-stack educational e-commerce site using Go, ReactJS, and MongoDB, managing the project from domain registration to deployment.

  • Implemented secure and scalable RESTful APIs, optimized frontend responsiveness, and configured NGINX for load balancing and SSL.

Let's Connect

Open to collaborations, mentorship, and research opportunities in Full Stack Development, AI, Machine Learning and Computational Biology.

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