Rajesh Sharma
Software & Data Solutions Engineer
Bridging logic, design, and data to deliver impactful software.
Software & Data Solutions Engineer
Bridging logic, design, and data to deliver impactful software.
I build intelligent, scalable, and automation-first systems that power real-time decisions, optimize processes, and unlock data-driven growth. From architecting multi-tenant platforms and orchestrating ETL pipelines to deploying NLP and LLM-powered applications, I bring together software engineering, data science, and cloud expertise to turn complex problems into seamless digital products. Whether it’s accelerating research with ML, scaling nonprofit platforms, or automating customer intelligence : I engineer solutions that create measurable impact.
Design and build scalable, responsive applications using React, Django, and RESTful APIs to balance performance with maintainability.
Develop ETL pipelines, automate multi-source ingestion (APIs, web scraping, databases), and deliver clean, structured data for analytics and ML.
Build models for classification, anomaly detection, and topic extraction using LLMs, Transformers, and traditional ML, focusing on impact and interpretability.
Deploy and monitor cloud-native apps using AWS (EC2, S3, Lambda), Docker, and CI/CD pipelines — optimizing performance and cost.
Create interactive dashboards with drill-down metrics, executive summaries, and real-time insights to support informed decision-making.
Architect secure, token-authenticated, modular systems that enable multi-tenant SaaS platforms, scalable microservices, and efficient backend design.
From Ideas to Deployments
Performed in-depth exploratory data analysis on Rent the Runway dataset, uncovering trends in customer behavior, product ratings, and fit satisfaction. Analyzed rental patterns across age groups, body types, and seasons. Applied sentiment analysis on reviews and visualized insights using 2D/3D plots to inform customer segmentation and occasion-based marketing strategies.
Designed a custom embedding approach for a bipartite ingredient-nutrient graph to represent nutritional relationships in lower-dimensional space. Built a biased random walk algorithm influenced by edge weights (normalized nutrition values) to better preserve feature significance during embedding. This technique improved ingredient clustering for dietary recommendation systems.
Built an NLP-powered pipeline to extract executive names and job titles (e.g., CEO, VP) from M&A press releases using web scraping, Named Entity Recognition, and relationship extraction. Automated the analysis of SEC filings and business blogs to identify key delegates involved in high-value deals, reducing manual effort in business intelligence workflows.
Built a bipartite graph-based system to recommend meal plans based on nutritional values and ingredient compatibility. Designed a custom graph embedding (not based on conventional DeepWalk) and applied K-Means clustering to group similar ingredients. Enabled allergy-aware substitutions for dietary constraints. The model supports ingredient-level personalization and aims to assist hospitals and individuals in preparing nutrition-optimized recipes with minimal human intervention.
Developed a recommendation system using H&M’s customer, article, and transaction data (31M+ records) to generate personalized fashion suggestions based on purchase history and demographic clusters. Leveraged association rules, unsupervised clustering (by age), and metadata preprocessing to enhance the shopping experience and reduce decision fatigue. Optimized data handling using GPU-based processing (cudf) and memory-efficient formats (.parquet) for scalable insights.
Skilled in full-stack engineering, machine learning, data engineering, and cloud deployment. I bring a product-first mindset and engineering depth to solve business, research, and nonprofit challenges at scale.
MS in Computer Science - Indiana University Bloomington
Specialization Data Science & AI - IIIT Delhi
B.Tech in Computer Science - Guru Nanak Dev University
Let’s build something meaningful together. Whether it’s an idea, project, or collaboration, I’m just a message away.