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Yoshika Verma

Machine learning internship @NEETprep|| AI/ML Engineer | Deep Learning · NLP · Computer Vision | Python · PyTorch · TensorFlow | Interned @ IIT Jammu · ISI Kolkata · NEETprep | NIT Jalandhar ’26

Jalandhar

3+ years of work experience

NEETPrep GoodEd Technologies Private Limited
Jan 20267 mosJul 2026

Built production data infrastructure and analytics tooling for one of India's largest EdTech platforms. • Engineered automated ETL pipelines syncing HubSpot CRM ↔ PostgreSQL, eliminating 8+ hrs/week of manual data work across 3 platforms • Shipped a real-time Next.js analytics dashboard for lead conversion tracking — enabling sales to prioritise prospects 2× faster • Designed multi-persona social media automation strategy across 4 brand accounts, increasing content output by 60% Stack: Python · Next.js · PostgreSQL · HubSpot API · REST APIs
Indian Statistical Institute, Kolkata
Jun 20253 mosAug 2025

Kolkata, West Bengal, India

Worked on a cutting-edge biomedical ML project combining imaging and clinical data for neurological disease diagnosis. • Built a multimodal Parkinson's Disease detection model fusing MRI image features (CNN) with clinical tabular data (XGBoost) — AUC 0.91 on a 500-patient dataset • Reduced model inference latency by 35% through feature selection and pipeline optimisation — viable for near real-time clinical screening • Presented methodology in research review; adopted as lab baseline for ongoing biomedical ML programme Stack: Python · TensorFlow · PyTorch · XGBoost · CNN · Scikit-learn · Pandas · Seaborn
CognoRise InfoTech
Aug 20242 mosSep 2024

Online

Indian Institute of Technology Jammu
Jun 20242 mosJul 2024

Designed, trained, and benchmarked end-to-end ML pipelines on real-world datasets in a research environment. • Built and compared 5 classifiers (Random Forest, SVM, XGBoost, LSTM, CNN) — top model hit 94% accuracy and 0.93 F1-score • Automated evaluation reporting with Pandas + Seaborn, cutting report generation from 3 hrs → under 20 minutes per experiment cycle • Evaluated models using accuracy, precision, recall, F1, AUC, and confusion matrix — full production-grade assessment Stack: Python · Scikit-learn · XGBoost · TensorFlow · LSTM · Pandas · NumPy · Matplotlib
Dr. B R Ambedkar National Institute of Technology, Jalandhar ( PUNJAB)
Nov 20223 yrs 8 mosJun 2026

Dr. B R Ambedkar National Institute of Technology, Jalandhar ( PUNJAB)
Nov 20221 yr 9 mosJul 2024

Yoshika’s AI Stack

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Education

Dr. B R Ambedkar National Institute of Technology, Jalandhar ( PUNJAB)

Bachelor of Technology - BTech, Biotechnology

Dr. B R Ambedkar National Institute of Technology, Jalandhar ( PUNJAB)

20224 yrs2026

12, Non medical

APOLLO PUBLIC SCHOOL

20201 yr2021

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Headline

Machine learning internship @NEETprep|| AI/ML Engineer | Deep Learning · NLP · Computer Vision | Python · PyTorch · TensorFlow | Interned @ IIT Jammu · ISI Kolkata · NEETprep | NIT Jalandhar ’26

About

I build ML systems that work in the real world — not just on notebooks. In the last 2 years, I've interned across 3 research and industry environments: IIT Jammu, ISI Kolkata, and NEETprep. Each one taught me something different — academic rigour, biomedical deep learning, and shipping production data pipelines under real business pressure. Here's what I've actually shipped: → Multimodal Parkinson's Disease detection model (CNN + XGBoost) — AUC 0.91 on 500-patient dataset @ ISI Kolkata → Automated ETL pipelines syncing HubSpot + PostgreSQL, saving 8+ hrs /week of manual work @ NEETprep → 5-model ML benchmark (RF, SVM, XGBoost, LSTM, CNN) with 94% accuracy @ IIT Jammu → Full-stack hotel booking platform — Next.js, REST APIs, Google Apps Script, end-to-end solo build My stack: Python · PyTorch · TensorFlow · XGBoost · SQL · Pandas · Scikit-learn · Next.js · PostgreSQL · Tableau · Power BI I'm currently in my final year of B.Tech (Biotechnology + ML focus) at NIT Jalandhar, graduating in 2026. My biotech background gives me an edge in healthcare AI and biomedical data problems — a niche most ML engineers don't have. Open to: AI/ML Engineer · Data Scientist · ML Intern roles (full-time or 6-month internship) at product and service companies. Let's connect if you're hiring or building something interesting.

Location

Jalandhar

AI stack

cursor

opencode

claudecode

Work experience

Machine Learning Intern at NEETPrep GoodEd Technologies Private Limited, Jan 2026 - Jul 2026 · 7 mos, Built production data infrastructure and analytics tooling for one of India's largest EdTech platforms. • Engineered automated ETL pipelines syncing HubSpot CRM ↔ PostgreSQL, eliminating 8+ hrs/week of manual data work across 3 platforms • Shipped a real-time Next.js analytics dashboard for lead conversion tracking — enabling sales to prioritise prospects 2× faster • Designed multi-persona social media automation strategy across 4 brand accounts, increasing content output by 60% Stack: Python · Next.js · PostgreSQL · HubSpot API · REST APIs

Summer Intern at Indian Statistical Institute, Kolkata, Jun 2025 - Aug 2025 · 3 mos, Kolkata, West Bengal, India, Worked on a cutting-edge biomedical ML project combining imaging and clinical data for neurological disease diagnosis. • Built a multimodal Parkinson's Disease detection model fusing MRI image features (CNN) with clinical tabular data (XGBoost) — AUC 0.91 on a 500-patient dataset • Reduced model inference latency by 35% through feature selection and pipeline optimisation — viable for near real-time clinical screening • Presented methodology in research review; adopted as lab baseline for ongoing biomedical ML programme Stack: Python · TensorFlow · PyTorch · XGBoost · CNN · Scikit-learn · Pandas · Seaborn

Data Scientist at CognoRise InfoTech, Aug 2024 - Sep 2024 · 2 mos, Online

Intern at Indian Institute of Technology Jammu, Jun 2024 - Jul 2024 · 2 mos, Designed, trained, and benchmarked end-to-end ML pipelines on real-world datasets in a research environment. • Built and compared 5 classifiers (Random Forest, SVM, XGBoost, LSTM, CNN) — top model hit 94% accuracy and 0.93 F1-score • Automated evaluation reporting with Pandas + Seaborn, cutting report generation from 3 hrs → under 20 minutes per experiment cycle • Evaluated models using accuracy, precision, recall, F1, AUC, and confusion matrix — full production-grade assessment Stack: Python · Scikit-learn · XGBoost · TensorFlow · LSTM · Pandas · NumPy · Matplotlib

Alumni @Dr. BR Ambedkar National Institute of Technology jalandhar at Dr. B R Ambedkar National Institute of Technology, Jalandhar ( PUNJAB), Nov 2022 - Jun 2026 · 3 yrs 8 mos

Sophomore at Dr. B R Ambedkar National Institute of Technology, Jalandhar ( PUNJAB), Nov 2022 - Jul 2024 · 1 yr 9 mos

Education

Bachelor of Technology - BTech, Biotechnology, Dr. B R Ambedkar National Institute of Technology, Jalandhar ( PUNJAB)

12, Non medical, APOLLO PUBLIC SCHOOL