Actively looking for a job
Pratiksha Pradhan
Data Analytics❘Northeastern University
Boston MA, United States
Education
Data Analytics
Experience
Data Engineering Intern at Digit Insurance
Executed a file ingestion module in DBeaver and PostgreSQL by deploying Psycopg2 and SQLAlchemy, to load structured files into the database from remote locations, add details to an audit table, and send email alerts regarding the same.
Intern at Indian Institute of Technology, Roorkee
● Extracted 20K+ Covid-related tweets through SNScrape to assess the impact of Covid cases on social media posting using Python ● Performed reverse geocoding through GeoPy and Nominatim to determine where in India people were tweeting more often ● Co...See more
Projects
Hands Me Down
Northeastern University
● Designed conceptual data models and mapped it to a relational model to build the database for a recommerce platform ● Executed relational model via MySQL and non-relational model via NoSQL in MongoDB to query data ● Accessed the database via Python and created Matplotlib visualizations to gain insights such as monthly change in new clients
https://github.com/ppratiksha95/Hand-Me-DownsGender Recognition Using Speech Signal Processing
Delhi Technological University
● Conducted data preprocessing, used librosa and ffmpeg to produce functions to extract features from each audio sample ● Developed a deep-feed forward neural network model with five hidden layers to predict the gender of the voice input ● Facilitated the testing of the model by inputting own voice using torchaudio, IPyWebRTC, IPython, with an accuracy of 85%
https://github.com/ppratiksha95/Gender-Recognition-using-Speech-Signal-ProcessingDetection of Polycystic Ovary Syndrome
Northeastern University
• Performed data visualization, oversampling, data partitioning, standardization and scaling, and dimension reduction on dataset • Implemented machine learning models like logistic regression, gradient boost, classification trees, Naïve Bayes using sklearn along with hyperparameter tuning, recursive feature elimination, k-fold cross validation to find the best classification model • Evaluated and visualized model performance to conclude that gradient boost is the best algorithm with a sensitivity of 90%
https://github.com/ppratiksha95/Detection-of-PCOSLanguages
English
Professional
Hindi
Professional
Skills
Python
R
SQL
NoSQL
Tableau
Power BI
Datawrapper
MATLAB
Spreadsheet Applications like MS Excel
Document Applications like MS Word
Presentation Applications like MS PowerPoint
Communication Skills
Presentation Skills
Leadership
Teamwork
Interests
- Data Science & Math