Madisetty Padmavathi
Summary
• Total 9 years of experience which includes 3 years of experience in Data Science, Machine
Learning, Deep Learning, Natural Language Processing algorithms.
• I have utilized BERT and RoBERTa transformer models in various natural language
processing tasks during my work.
• Working experience and extensive knowledge in Python with libraries such as Scikit-
learn, Tensorflow, PyTorch, Numpy, Pandas, Matplotlib, Seaborn. NLT
• Used Machine Learning algorithms to successfully deliver predictive maintenance project.
• Worked on tools like Pycharm, Jupyter Notebook and Visual Studio.



Technical
Summary
Programming Languages :
Python
Libraries :
Pandas, Numpy,
Scipy, NLTK,
Transformers
Frameworks
:Scikitlearn,
Tensorflow,
keras Supervised
Machine Learning:
Liner Regression,
Naive Bayes,
SVM, KNN,
Decision
Trees, Random
Forest,
XGBoost etc.
Unsupervised Machine
Learning: KMeans,
Hirerachial
Clustering,
DB Scan Deep
Learning Neural
Networks, CNN,
RNN,
LSTM,Word2vec,
Word
Embeddings
, Transformer
models, BERT,
RoBERTa,
VGG-16,AlexNet
Data Visualization
libraries: Matplotlib,
seabor
n Versioning : Git
Coding Environment:
Jupyter notebook,
Pycharm, VS
Code
Chat
boat developer
• Recognized and got appreciated by clients to deliver efficient solutions.
• Have excellent communication, analyzing and predicting skills.
Work Experience
Webority Technologies Pvt.Ltd
Data Scientist August 2020 - Present
Project 1: Predictive maintenance of manufacturing equipment. This project is to predict the equip-
ment failures and reduce the downtime in the production process using sensor data and
historical maintenance records.
Roles and Responsibilities
• Actively involved in daily standup calls and on assigned tasks.
• Analyze and filtered the data sent by clients in multiple batches.
• Optimized and Pre-processed the data before building the classification model.
• Performed feature engineering on the data using Python libraries like Numpy, Pandas and Seaborn.
• Built and trained the model using Random Forest classification and XG boost classification.
• Analyzed model prediction accuracy using accuracy Classification Reports, Confusion Matrix

Project 2: Customer feedback analysis for quality improvement. Main aim of this project is to auto-
mate the customer feedback analysis using Natural Language Processing (NLP) to improve the
quality of the products.
Roles and Responsibilities
• Performing Text-Preprocessing like cleaning and preparing the text data for analysis (such as
removing stop words, punctuation’s and special characters and converting text to
lowercase.
• Built and trained the model using Naïve Bayes and Support Vector Machines (SVM’s).
• Collaborating with cross-functional teams such as product development, marketing and cus-
tomer service to implement the changes based on the insights gained from the analysis.
• Continuously monitoring and evaluating the effectiveness of changes made and refining
the models accordingly.

Data Science Intern May 2019 - May 2020
Ineuron
• Implemented Machine Learning models on different problem statements (classification and
regression) and increased the accuracy by using hyper parameter tuning (Grid Search CV)
• Improved the accuracy of email classification from 85% to 95% through feature
engineering and regularization techniques (Deep Learning).
• Car price prediction using Machine Learning algorithms.

• Technologies used: Python, Machine Learning models (Supervised and unsupervised), Deep
learning (ANN and CNN), NLP (tokenization, stemming, lemmatization), visualization tools
like Matplotlib and seaborn.
Idexcel Technologies - Lead Recruiter June 2016 - Oct 2017
Hyderabad
– Involved in End-to-End Recruitment.
– Recruitment which involves sourcing, head hunting, scrutinizing short listing resumes
from entry level to Sr. Management Level positions.
– Conducting telephonic interviews and taking care of the entire selection process in
close coordination with the candidates for different positions.
– Conducting referral check for the candidates (if required).
Spectrosign- Team Lead, Recruiter July 2015 - May 2016
Hyderabad
– Involved in complete end to end recruitment’s (from requirement gathering from hiring
managers to closing that position in TAT)
– Motivating and leading the team of 4 recruiters
Saket Infospace- Recruitment Lead March 2013 - June 2015
Hyderabad
– Involved in complete end to end recruitment’s
– Motivating and leading the team
Blossom Tech Solutions- Sr. HR Recruiter Feb 2011 - March 2013
Hyderabad
– Involved in complete end to end recruitment’s
– Conducting referral check for the candidates.
Education

2006 - 2008 MBA, Kandula School of Management, Kadapa, Andhra
Pradesh

Human Resources Management and Finance Management
2004 - 2006 Graduation, Vikas Degree College, Kadapa, Andhra Pradesh

Maths, Physics and Electronics

Research Publications under review
1. Explainable Detection of Online Sexism (EDOS). [Implemented using Transformer based mod-
els BERT and RoBERTa]
2. Multi-Label and Multi-Class Emotion Classification on Code-Mixed Text Messages.[Implemented
using Transformer based models BERT and RoBERTa]