Pallabi Mallick

Kolkata

Summary

Motivated and detail-oriented aspiring data analyst with a strong foundation in data analysis and visualization. Skilled in Python (Pandas, NumPy, scikit-learn) and SQL, with hands-on 2 years' experience in Oracle ERP HRMS, including Core HR and Payroll. Adept at identifying trends and delivering actionable insights to support business decisions. Currently advancing expertise in Machine Learning to enhance analytical capabilities and solve complex problems.

Overview

years of professional experience

Certification

Work History

Oracle EBS Configuration specialist

Cognizant

07.2022 - Current

Provided functional and technical support for Oracle HRMS modules, including Core HR, Payroll, and Self-Service.
Managed timecard entry and workflow issue resolution within the HR module.
Monitored, maintained, and troubleshot 20+ Autosys jobs per week, identifying and resolving 100% of job failures within10-15 min, ensuring smooth ERP functionality. Collaborated with HR and IT teams to optimize HR workflows and enhance system performance.
Utilized ServiceNow and Jira to manage 90+ tickets monthly, ensuring 90% timely resolution and optimized ERP system efficiency.

Education

Diploma - Computer Science and Technology

APC Roy Polytechnic

07.2022

Bachelor of Technology - Computer Science and Engineering

Government College of Engineering And Leather Technology

05.2019

Skills

Data Analysis

Data Visualization

Database management

Programming

Soft Skills

Certification

Become a Data Analyst - (Python, Excel, SQL, Power BI), Udemy
Complete Data Analyst Bootcamp from Basics to Advanced, Udemy
Microsoft Access: Complete MS Access Mastery for Beginners, Udemy

Technical Skills & Tools

Excel, Excel Macros, Google Sheets, Power BI
SQL Developer, Microsoft Access, MySQL Workbench
Python, SQL/PLSQL, MySQL, Java, HTML

Languages

English

Hindi

Bengali

Project

Employee Attrition Prediction (HR Analytics)

Analyzed 1,470+ employee records to identify key factors influencing attrition.
Performed data cleaning, feature engineering, and EDA using Pandas, Seaborn, Matplotlib, NumPy, and Label Encoding.
Built a Logistic Regression model, achieving 85% accuracy in predicting employee attrition.
Developed Power BI dashboards to visualize attrition trends by department, job role, gender, and education level and analyzed survey scores for attrition insights.
Provided data-driven recommendations, enabling HR teams to implement strategies that reduced attrition by 10%.

Timeline