Open to Full-Time · Dec 2026

Nipun
Navadia

Data Scientist & AI Engineer

Published researcher · 43 citations · h-index 4.
Triple-degree technologist with 4+ years at Capgemini building enterprise security systems and ML pipelines, now finishing MS Data Science at Pace University.

⭐ 43 Citations h-index 4 9 Publications
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About Me

Where Security Meets
Intelligence

I'm Nipun Navadia, a published AI researcher and cybersecurity practitioner, completing my MS in Data Science at Pace University (Dec 2026), while holding an MTech in Software Systems from BITS Pilani and a BTech in Computer Science.

At Capgemini, I spent 4 years building enterprise security systems: investigating high-priority incidents alongside CISOs and DPOs, eliminating 750K+ vulnerabilities, and automating operations across 20,000+ machines. I know what shipping under real pressure means.

In parallel I've been publishing peer-reviewed research on AI, deep learning, IoT security, and autonomous systems. 43 citations, h-index 4. My 2025 papers on Explainable AI for IoT intrusion detection reflect where I'm headed: intelligent, interpretable security systems.

Based in New York, NY. Open to full-time roles in AI/ML engineering, data science, and cybersecurity, especially where they intersect.

New York, NY nipunnavadia@gmail.com Google Scholar ↗
📚
Published Researcher
9 publications across AI, cybersecurity, IoT, and deep learning. 43 citations, h-index 4, i10-index 2.
🛡️
Enterprise Security Veteran
4 years in SOC operations, incident response, SIEM analysis, and large-scale vulnerability management at Capgemini.
🤖
Applied ML Builder
Classification benchmarking, time-series forecasting, explainable AI. Hands-on with Python, PyTorch, scikit-learn.
Automation at Scale
PowerShell automation rebooting 20,000 machines. I systematically replace manual work with intelligent systems.
Education

Triple-Degree Foundation

Software engineering depth, AI/ML methods, and enterprise security expertise, across three institutions on two continents.

Pace University · New York, USA
Master of Science
Data Science
Graduating Dec 2026
Seidenberg School of CS & Information Systems. Machine learning, statistical modeling, AI engineering, data pipelines.
Machine LearningStatisticsAI Engineering
BITS Pilani · India (WILP)
Master of Technology
Software Systems
Completed Jul 2024
Work-Integrated Learning Program. Advanced software engineering, system design, and enterprise architecture alongside industry experience.
Software ArchitectureSystems Design
AKTU · Dronacharya Group · India
Bachelor of Technology
Computer Science & Engineering
Completed Sep 2020
Strong CS fundamentals in algorithms, data structures, networking, and operating systems.
Computer ScienceNetworking
Professional Experience

4 Years at Capgemini

From software engineer to associate consultant, shipping at enterprise scale across security operations, automation, and data intelligence.

Jul 2023 – Jan 2025 · 1.5 yrs
Associate Consultant
Capgemini
  • Investigated high-priority security incidents alongside CISOs, DPOs, and CISAs using Splunk SIEM and forensics tools (Magnet AXIOM, Autopsy), from evidence acquisition through executive-ready remediation reports.
  • Guided Level 1 & Level 2 SOC teams resolving security alerts, analyzing SIEM logs with SQL queries and escalating critical incidents using Splunk ES and CrowdStrike Falcon.
  • Performed statistical analysis in Python & Pandas to identify incident trends, informing proactive improvements to enterprise threat posture.
Splunk ESCrowdStrike FalconMagnet AXIOMAutopsyPythonPandasSQLForensics
Jan 2023 – Jun 2023 · 6 mos
Senior Software Engineer
Capgemini
  • Led vulnerability management via Agile + ServiceNow, remediating 750K+ vulnerabilities with 97% risk reduction. Applied logistic regression in Python to intelligently prioritize remediation efforts.
  • Reduced costs by 20% by automating remote reboots of 20,000 machines via PowerShell jump server automation, eliminating manual Windows operations.
  • Built custom Qualys dashboards for real-time vulnerability monitoring, remediation tracking, and C-suite operational visibility.
QualysServiceNowPowerShellPythonLogistic RegressionAgile
Apr 2021 – Dec 2022 · 1.75 yrs
Software Engineer
Capgemini
  • Identified and remediated security vulnerabilities through OS and application patching across large enterprise fleets.
  • Enhanced security posture by 25% through structured remediation, addressing 50,000+ vulnerabilities across multiple systems within two months using Qualys tracking.
QualysOS PatchingVulnerability TrackingSecurity Hardening
Featured Projects

ML Systems Built

End-to-end machine learning pipelines and data science solutions grounded in real datasets and measurable outcomes.

🏦
ML Model Benchmarking Bank Marketing Dataset
Classification · Comparative Analysis · Feb–Apr 2025
Benchmarked six supervised classification algorithms on 45,211 records to predict term deposit subscriptions. Full ROC-AUC, F1, precision/recall evaluation suite with stratified splits and cross-validation to select the optimal customer-targeting model.
6
Models Benchmarked
45K
Records Analyzed
ROC-AUC
Primary Metric
PythonScikit-learnPandasXGBoostRandom ForestLogistic RegressionNaive BayesKNN
NYC Electricity Demand Forecasting
Time Series · Facebook Prophet · Apr–May 2025
ETL pipeline to clean and aggregate daily/monthly/yearly electricity usage across all NYC boroughs. Facebook Prophet with tuned seasonality and changepoints, validated with MAE, MAPE, R².
5
NYC Boroughs
3
Forecast Horizons
PythonFacebook ProphetPandasETLSeaborn
🛡️
Vulnerability Intelligence Dashboard
Cybersecurity · Enterprise · Capgemini
Custom Qualys dashboards and automated reports for real-time vulnerability monitoring. ServiceNow integration for seamless ticket-to-patch lifecycle. 750K+ vulnerabilities tracked across enterprise client environments.
750K+
Vulns Tracked
97%
Risk Reduction
QualysServiceNowPowerShellSQLPower BI
Innovation Lab

Research & Publications

9 peer-reviewed publications spanning AI, deep learning, IoT security, cloud computing, and autonomous systems with co-authors at Amity University and international institutions.

0
Total Citations
0
h-index
0
i10-index
0
Publications
Research Areas
Artificial Intelligence Machine Learning Cyber Security IoT Security Cloud Computing Deep Learning Explainable AI
Applications of AI in Agriculture
⭐ 14 citations 2022
Challenges and Opportunities for Deep Learning Applications in Industry 4.0
T Singh, H Bhadwaj, L Verma, NR Navadia, D Singh, A Sakalle, ...
AI in AgricultureDeep LearningIndustry 4.0
Applications of Cloud-Based Internet of Things
⭐ 10 citations 2021
Integration and Implementation of the Internet of Things Through Cloud Computing
NR Navadia, G Kaur, H Bhardwaj, T Singh, A Sakalle, D Acharya, ...
Cloud ComputingIoT
Covid-19: Machine Learning Algorithms to Predict Mortality Rate for Advance Testing and Treatment
⭐ 6 citations 2021
Soft Computing for Problem Solving: Proceedings of SocProS 2020, Volume 2
NR Navadia, G Kaur, I Malik, L Verma, T Singh, H Bhardwaj
Machine LearningHealthcare AICOVID-19
Effects of SARS-COV-2 on Blood
⭐ 6 citations 2021
Soft Computing for Problem Solving: Proceedings of SocProS 2020, Volume 2
I Malik, NR Navadia, A Jamshed, L Verma, T Singh, H Bhardwaj
Medical AISARS-CoV-2
A Critical Survey of Autonomous Vehicles
⭐ 3 citations 2021
Cyber-Physical, IoT, and Autonomous Systems in Industry 4.0, pp. 235–254
NR Navadia, G Kaur, H Bhardwaj, A Sakalle, Y Singh, T Singh, ...
Autonomous VehiclesCyber-Physical Systems
Brain Hemorrhage Detection Using Deep Learning: Convolutional Neural Network
⭐ 3 citations 2021
International Conference on Information Systems and Management Science, pp. 565–570
NR Navadia, G Kaur, H Bhardwaj
Deep LearningCNNMedical Imaging
CloudConsumerism: A Consumer-Centric Ranking Model for Efficient Service Mapping in Cloud
⭐ 1 citation 2022
Mobile Information Systems 2022 (1), 5960976
Neeraj, N Garg, NR Navadia, A Lakhanpal, I Gupta, W Ibrahim, M Raj
Cloud ComputingRanking Models
Analyzing the Role of LIME and SHAP in Explainable DoS Attack Detection for IoT Systems
New · 2025
2025 4th International Conference on Automation, Computing and Renewable Systems
A Paul, S Kumari, NR Navadia, S Sinha
Explainable AILIMESHAPIoT SecurityDoS Detection
Explainable Intrusion Detection System for Internet of Things: Explainability with Reliability
New · 2025
2025 5th International Conference on Soft Computing for Security
A Paul, S Kumari, NR Navadia, S Sinha
Intrusion DetectionExplainable AIIoT SecurityReliability
Technical Arsenal

The Stack

Battle-tested across enterprise security operations and applied ML every tool here has been shipped with in production.

Languages & Core
PythonSQLPowerShellVibe Coding
ML & AI
Scikit-learnPyTorchTensorFlowKerasXGBoostFacebook ProphetLLMsPrompt Engineering
Cybersecurity
Splunk ESCrowdStrike FalconMagnet AXIOMQualysAutopsySIEMThreat IntelligenceIncident Response
Data & Visualization
NumPyPandasMatplotlibSeabornPower BITableau
ML Methods
ClassificationTime SeriesPCAK-MeansRandom ForestsSVMCNNXAI
Tools & Platforms
ServiceNowAgile / ScrumGitRelational DBsETL PipelinesCloud (AWS/Azure)
Available · Graduating Dec 2026
Let's Work Together
Open to full-time roles in Data Science, AI/ML Engineering, and Cybersecurity especially where they intersect. Also open to research collaborations on explainable AI and IoT security.