Sai Sri
Data Scientist - AI/ML | AI Researcher | Immediately available for Full time/contract roles
- Role
- Graduate Research Assistant at Texas State University Computer Science
- Location
- Austin, TX, US
- LinkedIn followers
- 500 followers
About Sai Sri
I am passionate about solving complex problems through data-driven solutions, intelligent systems, and scalable software. With a strong foundation in Python, SQL, cloud platforms (AWS, GCP), and machine learning frameworks (PyTorch, TensorFlow), I’ve built and deployed real-time ML pipelines, interactive dashboards, and large-scale data workflows for research and production environments. I bring hands-on experience from my roles as a Graduate Research Assistant and Applied Machine Learning Engineer, where I worked on projects involving generative AI, model deployment (MLOps), data lake architecture, and API integration. I’m also proficient in tools like Power BI, Tableau, Git, Docker, and Kubernetes. I thrive in collaborative environments, enjoy working at the intersection of data and software, and am currently seeking full-time or internship opportunities in software engineering, data engineering, or AI/ML roles. Let’s connect if you\'re looking for a technically strong and highly motivated problem-solver who\'s ready to contribute from day one.
Experience
Graduate Research Assistant
Texas State University Computer Science
Aug 2024 — Present · San Marcos, TX, US
Developed deep learning models for intrusion detection, focusing on detecting anomalies in computer networks using frameworks like TensorFlow and PyTorch. My work involves data preprocessing, feature engineering, and exploratory analysis of network datasets utilizing Python libraries such as pandas, NumPy, and Scikit-learn. Additionally, I prepare research findings for academic presentations and publications, creating clear and impactful visualizations with Python data visualization tools and Tableau.
Education
Texas State University
Master's degree
2023 — 2025
Lovely Professional University
Computer Science and Engineering
2019 — 2023
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