I'm a Mathematics & Scientific Computing student focused on data science and backend engineering. My work centers on building data pipelines, designing REST APIs, and applying statistical methods to extract insight from real-world datasets — with a mathematical background that shapes how I think about model design, data quality, and performance trade-offs.
Currently moving from descriptive analysis toward predictive systems — deepening my work in machine learning and building models that forecast and classify rather than just describe.
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Data Science & Analytics
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Backend & APIs
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DSA & Tools
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An asynchronous backend microservice that ingests live market data and computes the mathematically optimal capital allocation across a multi-asset portfolio. An
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A high-performance microservice that computes the mathematically optimal price for products to maximize profit. Uses SciPy's
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An end-to-end data science pipeline and REST API for customer segmentation. Processes 100,000+ real-world e-commerce transactions to compute Recency, Frequency, and Monetary scores and classify customers into actionable business segments in real time. A key EDA finding — over 95% of customers had made only a single purchase — required custom scoring functions outside standard quantile methods to meaningfully isolate high-value segments from the broader one-time buyer pool.
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Currently building out additional projects in machine learning and applied statistics. New work gets pushed regularly — the full, up-to-date list always lives on my portfolio site. |
| Area | Focus |
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| SQL | Query optimization and large-scale structured datasets |
| Scikit-Learn | Supervised and unsupervised learning pipelines |
| ML Fundamentals | Regression, classification, and clustering — with emphasis on underlying mathematics |
| Pipeline Optimization | Applying scientific computing principles to data processing efficiency |
- LinkedIn: linkedin.com/in/yash-raj-49xe
- Twitter / X: @Yash_49_Xe
- LeetCode: leetcode.com/u/Yash_xe--49
- Email: yashraj4009.xe@gmail.com