Pavan Kumar S
Bangalore
Summary
Analytical and detail-oriented customer care representative seeking to transition to a data scientist role. Skilled in data analysis, statistical modeling, and programming languages. Excels at problem-solving and communicating insights to diverse stakeholders. Adept at using data to improve customer satisfaction, reduce churn, and increase revenue. Completed relevant coursework in Lachine learning, Artificial Intelligence, Tableau and Power Bi. Strong work ethic and ability to learn quickly.
Overview
2
2
years of professional experience
1
1
Certification
Work History
Data Scientist Intern
Innodatatics Inc
10.2022 - Current
- Successfully completed three end-to-end live projects as a Data Science Intern.
- Utilized tools and technologies such as Python, scikit-learn, TensorFlow, and spaCy to develop solutions for real-world challenges.
- Projects included automated steel product counting using image recognition, solar panel fault prediction, and named entity recognition for medical curation.
- Demonstrated expertise in data preprocessing, model development and evaluation, and deployment using frameworks like Flask and Streamlit.
- Made significant contributions to improving operational efficiency, reducing costs, and generating revenue through the implementation of data-driven solutions.
Customer Care Associate
Zingfin Internet Pvt Ltd
11.2021 - Current
- Recognized as a top-performing Customer Care Associate, consistently ranked within the top 3 employees for four consecutive months.
- Demonstrated exceptional customer service skills by efficiently handling customer inquiries, addressing questions, and resolving problems promptly.
- Consistently met or exceeded performance targets, displaying a strong work ethic and dedication to providing excellent service.
- Collaborated with team members to streamline processes and improve overall customer experience.
Education
Data Science | Deep Learning | AI -
10.2022
Data Visualization Using Tableau -
09.2022
Bachelor of Science - Electroincs, Physics, Mathematics
04.2021
Skills
- Python
- Statistical Analysis
- Analysis skills
- Machine learning
- SQL
- NLP
- Tableau
- Power Bi
- SpaCy
- Flask
- Deep Learning
- OpenCV
- NLTK
- YOLO
- Transformers
- Object Detection
- Image Processing
- Cryptocurrencies and Blockchain
Certification
Data Science - IBM
Data Science and Deep Learning - Universiti Teknologi Malaysia
Data Science using Python & R Programming - 360DigiTMG
Articial Intelligence and Deep Learning Program - 360DigiTMG
Data Visualization Using Tableau - 360DigiTMG
Python Fundamentals - NASSCOM
Certificate Course on Data Science - NASSCOM
Languages
English
Bilingual or Proficient (C2)
Hindi
Advanced (C1)
Kannada
Bilingual or Proficient (C2)
Telugu
Bilingual or Proficient (C2)
Projects
Project: Automated Steel Product Counting Using Image Recognition
Problem: Manual counting of steel products in images is time-consuming, prone to errors, and reduces operational efficiency.
Solution: Developed a deep learning model using Python, TensorFlow, Keras, NumPy, Pandas, Yolo, RCNN Models, and deployed on AWS with Flask. The model accurately identifies the number of steel products in an image, reducing manual counting by 90% and improving operational efficiency. Achieved high accuracy (80%+) in product identification, enhancing inventory management and generating $100K annual profits by avoiding overstocking or stockouts.
Project: Solar Panel Fault Prediction
Problem: The company faces challenges with solar panel maintenance and downtime caused by difficult-to-detect faults, leading to high costs and revenue loss.
Solution: Developed a fault prediction model using Python, scikit-learn, and Random Forest algorithm, achieving 98% accuracy. Reduced maintenance costs by 25% and downtime by 20%, potentially resulting in a revenue increase of $50K per annum. Future plans include extending the model to other installations and integrating it with real-time monitoring for predictive maintenance, saving up to $500K per annum.
Project: Named Entity Recognition for Medical Curation
Problem: The company is facing challenges with identifying and classifying medical entities such as diseases, symptoms, drugs, and treatments from the unstructured medical text. This is impacting the accuracy and efficiency of their medical curation process.
Solution: Developed an NER model using Python, NLP, spaCy, and Flask to accurately identify and classify medical entities in unstructured text, achieving 80% accuracy. Improved medical curation process with 30% fewer errors and 50% faster processing time, resulting in annual cost savings of $10,000.
Timeline
Data Scientist Intern - Innodatatics Inc
10.2022 - Current
Customer Care Associate - Zingfin Internet Pvt Ltd
11.2021 - Current
360DigiTMG - Data Science | Deep Learning | AI,
360DigiTMG - Data Visualization Using Tableau ,
Oxford College of Science - Bachelor of Science, Electroincs, Physics, Mathematics
Hobbies
Chess
Cricket
Blockchain and Cryptocurrencies
Trading
Similar Profiles
Savyasachi RSavyasachi R
Intern at InnodataticsIntern at Innodatatics
Chimezie OnyemaChimezie Onyema
Data Scientist at INNODATATICS Consulting FirmData Scientist at INNODATATICS Consulting Firm
VENKATESHH SUGANDHAMVENKATESHH SUGANDHAM
Data Science Intern at InnodataticsData Science Intern at Innodatatics
Tanuja YadavTanuja Yadav
Senior SDTM Programmer at NOVO NORDISKSenior SDTM Programmer at NOVO NORDISK
Ranjith C ARanjith C A
Drug Pricing Analyst | Market Access (US Market) at RxBenefits Healthcare India Pvt LtdDrug Pricing Analyst | Market Access (US Market) at RxBenefits Healthcare India Pvt Ltd