Priyanka Manuja

Bengaluru, Karnataka, India

Summary

Highly skilled professional with a proven track record of leveraging data-driven insights to inform strategic business decisions. Effective communicator with a passion for translating technical findings into actionable insights for stakeholders. Seeking to contribute my analytical expertise and problem-solving abilities to a dynamic data-driven team.

Overview

years of professional experience

Certification

Work History

Application Developer

IBM India Pvt Ltd.

Bengaluru

10.2021 - Current

Developed and executed complex SQL queries to analyze large datasets. Extracted useful insights from different sources.
Developed code using SAS for matching, merging, string manipulation, Un delimiting, and transforming datasets to achieve desired results.
Migrated legacy codes coded in JCL to SQL which reduced the usage of CPU immensely by 35%.
Testing and quality checks for each fulfillment sent to the client which improved the correctness of the results by 15%.
Proficiently utilized PostgreSQL and Python scripting for intricate data manipulation, resulting in a 15% reduction in preparation time and substantial CPU usage savings during migration.
Increased efficiency through task automation.
Constructed high-quality solutions within the provided TAT for Ad-hoc business requirements. Addressed customer escalations, defects, and queries for the team and self.

Education

Dual Certificate Program in Data Science And Artificial Intelligence -

Boston Institute of Analytics

Bengaluru, KA

03-2024

Bachelor of Engineering - Information Science

Dayananda Sagar Academy of Technology And Mgmt

Bengaluru, KA

07-2021

Skills

Programming Languages: Proficiency in Python and R for data analysis, manipulation, and model development
Data Manipulation: Experienced in using Pandas and NumPy in Python, as well as data frame manipulation in R
Machine Learning: Proficient in implementing machine learning algorithms for predictive modeling, classification, and clustering tasks
Deep Learning: Familiarity with deep learning architectures such as CNNs and RNNs for image and text data analysis
Data Visualization: Experienced in creating insightful visualizations using libraries like Matplotlib, Seaborn, Tableau, and Power BI to effectively communicate complex findings
SQL and Database Management: Proficient in SQL for data retrieval, manipulation, and basic database management tasks

SAS: Proficiency in SAS for data analysis, statistical modeling, and reporting
Time Series Analysis: Experienced in time series modeling techniques such as ARIMA and SARIMA for forecasting
Natural Language Processing (NLP): Proficient in text preprocessing, sentiment analysis, and text classification using NLP techniques
Generative AI: Familiarity with GANs, VAEs, and text generation using transformers like GPT-2 and BERT
Data Science Tools: Skilled in using various data science tools and environments, including Anaconda, Jupyter Notebooks, and Google Colab

Certification

Google Cloud Certified Associate Cloud Engineer (ACE) (02/2024 - 02/2027)
Google Cloud Digital Leader (01/2024 - 01/2027)
The complete SQL Bootcamp (Udemy) (10/2023 - 12/2023)
Microsoft Excel Advanced Excel Formulas and Functions (Udemy)
Business Intelligence using PowerBI Workshop by Skill Nation

Personal Projects

Rummaging free Parking Spaces - Mask RCNN, Python, and Deep Learning

Giving a video input of a parking space, this software will give us the available parking slots through a notification SMS. This will help people in metropolitan areas to find a parking spot without any hassle.

E2E Cricket Data Analytics Project using Web scraping, Python, Pandas, and PowerBI

Data collection - Collected data using Bright data. It uses proxy networks for building web scrapers.
Data prep using Pandas - Transforming the JSON files into CSV files and adding additional columns, removing special characters using Jupyter Notebook.
Data transformation in Power Query - defining headers in tables, trimming the data in fields, removing duplicates, adding new conditional columns, splitting columns by delimiter, replacing values, renaming columns, etc
Data modeling and building parameters using DAX - Established relationship between tables in Model View. Created DAX measures in Report View to build actual measures.
Building visuals and dashboard in PowerBI
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Timeline