Hakima Banoo
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HakimaBanoo

Software Engineer · Full-Stack & Machine Learning

I build intelligent, scalable systems — from crisp React interfaces to deep learning models that detect anomalies where others see noise. Bridging the gap between elegant frontend craft and powerful backend intelligence.

Raised in the mountains of Ladakh, trained at NIT Srinagar & IIT Delhi — I approach engineering with patience, precision, and a love for solving problems that matter. Currently open to full-time roles in software engineering and AI/ML.

2+ Years Exp.
84% ECG Accuracy
+20% ML Boost
10+ Technologies
Hakima Banoo — Software Engineer
NIT Srinagar B.Tech · Information Technology
Open to Work
30%Faster Processing
100%Detection Recall
25%Less Compute Time
20%Accuracy Boost
9.2CGPA · Grade 12
01 — About Me

Who I Am &
What I Build

I'm a Full-Stack Software Engineer with a deep interest in Machine Learning and AI-driven systems. I graduated from NIT Srinagar with a B.Tech in Information Technology and have worked in production environments at HCLSoftware and conducted ML research at IIT Delhi.

My engineering philosophy is simple: write code that solves real problems beautifully. I love the intersection of frontend craft — where users interact with your work — and the intelligence of ML models, where data tells its own story.

From Ladakh, a region of extraordinary landscapes and quiet resilience, I bring a focused, methodical approach to complex problems. I believe the best software, like the best terrain, reveals depth the longer you explore it.

Fast Learner
🤝 Team Player
🎯 Result-Driven
🧠 ML Enthusiast
🌐 Full-Stack
🏔️ From Ladakh
Phone+91 8899854451
LocationLadakh, India
Status● Open to Opportunities
B.Tech — Information Technology
National Institute of Technology, Srinagar
Aug 2021 – Jul 2025 · Srinagar, India
Data Structures · Algorithms · Operating Systems · DBMS
PCM — Higher Secondary
Govt. HSS Trespone, Kargil
Jan 2020 – May 2021 · Kargil, India
⭐ CGPA 9.2
Physics · Mathematics · Chemistry · English
02 — Skills

My Technical Toolkit

⌨️
Languages
PythonJavaScriptJavaC++SQLGoC
🧩
Frameworks
ReactNode.jsAngularTensorFlowPandasNumPyScikit-learn
🛢️
Databases & Cloud
MongoDBMySQLDockerKubernetesGitGitHubLinux
🤖
AI / ML
Deep LearningAnomaly DetectionResNetIsolation ForestKNNLOFFeature Engineering
🌐
Web & Tools
HTMLCSSREST APIsPostmanJiraVS CodeJupyter
🤝
Soft Skills
CommunicationTeamworkAdaptabilityTime ManagementAgile / Scrum
03 — Experience

Where I've Delivered

HCLSoftware
Software Engineer II
Sep 2025 – Mar 2026
📍 Noida, India
Full-Time · On-site
  • Built production-grade frontend components — login & landing pages — using React, JavaScript, HTML & CSS, improving UX across core user flows
  • Designed and implemented backend REST APIs with Node.js and MongoDB database schemas to support full-stack feature delivery
  • Collaborated in cross-functional agile sprint cycles, contributing full-stack features from design handoff to deployment
ReactJavaScriptCSSNode.jsMongoDBAgile
IIT Delhi
Machine Learning Intern
Dec 2023 – Feb 2024
📍 Delhi, India
Internship · On-site
  • Developed end-to-end data preprocessing pipeline using Python, Pandas & NumPy for telephonic audio signal analysis at research scale
  • Achieved a 20% improvement in anomaly detection accuracy through advanced feature engineering and model selection
  • Built Matplotlib visualisation dashboards for model performance reporting, supporting research evaluation and documentation
PythonTensorFlowPandasNumPyMatplotlibML/AI
04 — Projects

Case Studies &
Outcomes

01
🎧 Machine Learning · Anomaly Detection
Telephonic Audio Anomaly Detection
Dec 2023 – Feb 2024 · Individual Research Project
Problem
Detecting anomalies in telephonic audio signals with high accuracy at scale
My Role
Sole engineer — pipeline design, modelling, optimisation, reporting
Challenges
High compute cost, low precision, large unprocessed dataset
Approach
Isolation Forest + LOF + Elliptic Envelope ensemble
Outcomes: 30% faster processing · 100% recall · 25% less computation time
PythonTensorFlowKNNNumPyIsolation ForestJupyter
02
🫀 Deep Learning · Healthcare AI
ECG Anomaly Detection
Dec 2024 – Feb 2025 · Individual Research Project
Problem
Classify abnormal heart patterns from 12-lead ECG signal data reliably
My Role
Full ML pipeline — data prep, model training, evaluation & tuning
Challenges
High training loss, class imbalance, complex multi-lead ECG signals
Approach
ResNet-based deep learning on supervised labelled ECG dataset
Outcomes: 84% validation accuracy · 60.5% recall · Loss 7.02 → 2.99 over 20 epochs
PythonTensorFlowResNetScikit-learnPandasJupyter
05 — Let's Connect

Let's Build Something
Great Together

I'm actively seeking full-time roles in software engineering and AI/ML. Whether you have an exciting project, a role to fill, or just want to talk tech — I'd love to hear from you.

hakimabanoo.jk.csrl@gmail.com
📞 +91 8899854451
📍 Ladakh, India