Rashi.C

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Rashi Chauhan

Data Science and AI/ML Engineer · Technical Consultant, Hewlett Packard Enterprise

Delhi, India | rashichauhan67@gmail.com

linkedin.com/in/rashi-chauhan-67rc | github.com/RashiChauhan67 | Google Scholar | rashichauhan67.github.io/Portfolio

Professional Summary

Data Science professional at Hewlett Packard Enterprise with experience in predictive modelling, time-series forecasting, machine learning and business intelligence. Evaluated 8 forecasting algorithms for banking analytics, developed 5 Power BI dashboards and built a customer churn model achieving approximately 89% validation accuracy. Published researcher in computer vision and deep learning. Skilled in Python, SQL, ETL development, data quality and model evaluation.

Technical Skills

Programming:
Python, SQL, JavaScript, TypeScript, C++, C
Machine Learning:
Predictive Modelling, Classification, Customer Churn Prediction, Time-Series Forecasting, Model Evaluation, Deep Learning
Analytics and Visualization:
Power BI, Dashboard Development, Forecast Performance Analysis, Actual-versus-Predicted Analysis, Data Visualization
Data Engineering:
ETL Pipeline Development, Data Ingestion, Data Transformation, Data Quality, DDL Generation, Schema Management, Pipeline Monitoring
Tools and Frameworks:
TensorFlow, Keras, PyTorch, scikit-learn, OpenCV, Ultralytics YOLO, Git, GitHub Actions, Docker, FastAPI, Vertica, Cloudian Object Storage, Langflow, LangChain, RAG

Experience

Technical Consultant | Hewlett Packard Enterprise (HPE) Aug 2025 – Present · Gurugram, India

  • Built a four-stage ETL pipeline moving millions of records from Cloudian object storage to Vertica, automating DDL generation and schema updates and cutting manual pipeline maintenance by ~60%.
  • Developed a customer churn prediction model on quotes, contracts and survey data, reaching ~89% validation accuracy to support customer retention analysis.
  • Engineered an automated Aadhaar masking pipeline at large scale for the LIC–HPE project, integrating AI-driven quality-control decisioning and manual verification to improve masking accuracy by ~15% and reduce processing turnaround time by ~20%.
  • Strengthened banking analytical pipelines with centralized error handling, unified execution-status tracking and automated stakeholder notifications, reducing pipeline failures by ~30%.
  • Developed custom workflow automation tools for the Project Management Office, removing recurring manual tasks and saving ~56 hours of effort per week.
  • Developed a retrieval-augmented generation (RAG) application for natural-language retrieval of technical project documentation, with automated ticket escalation and response workflows using Langflow, MailHog and Zammad.

AI/ML Internship Trainee | Hewlett Packard Enterprise (HPE) Feb 2025 – Jul 2025 · Gurugram, India

  • Developed and evaluated a forecasting pipeline across 8 machine learning algorithms for banking analytics, achieving 92.4% product-level forecasting accuracy.
  • Built 5 Power BI dashboards tracking forecasting outputs, actual-versus-predicted trends and product-level performance.
  • Diagnosed and resolved NaN predictions and dimensional mismatches, improving data quality and consistency in downstream forecasts.
  • Compared forecasting model performance to identify suitable approaches for product-level banking analytics.

Summer Research Intern | NIT Raipur May 2024 – Jun 2024 · Raipur, India

  • Designed FMANet, a multi-level fusion network reaching 95% accuracy on the Colorectal Histology Dataset and 97% on NCT-CRC-HE-100K, outperforming baseline models.
  • Proposed an attention-based deep neural network for kidney-ailment diagnosis, achieving 99.48% accuracy on CT imaging data.

Data Science Intern | Tata Power Delhi Distribution Limited Apr 2024 – May 2024 · New Delhi, India

  • Developed machine learning systems for switchgear automation, improving operational efficiency by 15%.
  • Built a solar-panel anomaly detection model to flag faults ahead of manual inspection.

Education

M.Tech, Data Science and AI (Online) | IIIT Dharwad Aug 2026 – 2028 (Expected)

B.Tech, Computer Science | Amity University, Noida 2021 – 2025

CGPA: 9.00 / 10

Selected Publications

  • Integrating Machine Learning for Optimized Credit Card Processing: Enhancing Acquisition, Approval, and Fraud Detection. WCONF, 2025.
  • Optimizing Cloud Resources for Financial Market Prediction: A Machine Learning Study on NVIDIA Stock Data. WCONF, 2025.
  • Cloud-Based SaaS Solutions for Predictive Sales Forecasting in E-Commerce. WCONF, 2025.
  • Reducing the Carbon Footprint of Data Centers: CNN-Transformer-Based Workload Prediction for Green Cloud Computing. International Conference on Computational Intelligence and Network Security, 2025.
  • Fused Multi-Level Attention Features with a Constraint Fusion Network for Colorectal Tissue Classification Using Histopathological Images. Computers and Electrical Engineering (Elsevier), 2025. DOI: 10.1016/j.compeleceng.2025.110296
  • Attention Based Deep Neural Network for Classification of Kidney Ailments Using CT Images. IEEE ICCCNT, 2024. DOI: 10.1109/ICCCNT61001.2024.10723909
  • Plant Disease Identification Using a Dual Self-Attention Modified Residual-Inception Network. IEEE ICUMT, 2023. DOI: 10.1109/ICUMT61075.2023.10333302

Achievements

  • Best Social Impact Project, TECHNOVATE'25 (Amity University), for the final-year project "Smart Recycling Bin"
  • Winner, FlyHigh Coding Challenge, selected for the 4.0 Tech Camp, Dubai
  • 2nd Place, Technopreneur Hackathon, 4.0 Tech Camp, Dubai

Certifications

  • NVIDIA-Certified Associate: AI Infrastructure and Operations, NVIDIA, 2025
  • CCNA: Introduction to Networks, Cisco, 2024