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Hello, My name is
ANKIT NEGI
Aspiring Data Scientist having 2+ years of experience as software engineer with hands-on project experience in machine learning, LLM fine-tuning, and full-stack development using Python and JavaScript. Passionate about solving real-world problems through data and learning new technologies.
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Skills Overview

Statistics

Descriptive Statistics
Inferential Statistics
Hypothesis Testing
ANOVA
T-test & Z-test
Probability & Distribution

Machine Learning

Supervised ML
Unsupervised ML
NLP
LLMs
Deep Learning
Neural Networks
Principal Component Analysis (PCA)

Programming Languages

Python
JavaScript
SQL

Visualization

Matplotlib
Seaborn

Database

SQL
Mongo DB
Experience
MOODRAA-E PLATFORM
Software Engineer
September 2022 - January 2023
Developed my team-work skills by working in close collaboration with my colleagues.
Daily maintenance of code, debugging issues and solving clients’ problems.
worked on mobile app development and created major features on it.
Optimizory
Software Engineer
September 2023 - Present
Collaboratively developed and maintained applications for the Jira Marketplace.
Worked on two key applications like PACT and Links Explorer, enhancing project management and issues exploration capabilities for users.
Contributed to improving the overall efficiency by 40% and optimized the speed of applications up to 60%, Improved performance of the development team through innovative solutions and effective collaboration.
Made Links Explorer the most used application for project management in Jira marketplace.
Featured Projects
FINE TUNED LLM MODEL FOR CHATBOT
Utilized the llama2finetune-v2 model as the base model for generative AI. Trained model on various PDF data like Python Programming, Software Engineering, Medical terminologies. Enhanced the model using specialized medical datasets to improve its performance in healthcare-related NLP tasks. Skilled in machine learning, fine-tuning models, and creating tokenization for predictions.
LLM
NLP
Deep Learning
Tokenization
Cancer diagnosis
Used K-Fold cross-validation technique to avoid overfitting, Designed and compared models like Support Vector Machine (SVM), Random Forest Classifier, and Logistic Regression.
Visualizations
K-Fold Cross-Validation
Support Vector Machine ( SVM )
Random Forest Classifier
Logistic Regression.
CREDIT CARD CAMPAIGN
Successfully analyzed Cancer diagnosis data and built a predictive model. Utilized interactive visualizations and data filters to enhance data exploration and inform decision-making. Used K-Fold cross-validation technique to avoid overfitting, Designed and compared models like Support Vector Machine (SVM), Random Forest Classifier, and Logistic Regression.
Supervised ML
Visualization
Standardization
Seaborn
Stratified Split
Ankit Negi
Data Scientist
nankit793@gmail.com
+91 8920249775