Car Price Prediction
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Summary
Developed a machine learning model to predict used car prices based on critical factors such as fuel type, kilometers driven, and registration year.
A results-driven Product Analyst and aspiring MBA candidate with a strong foundation in computer science and data analytics. Adept at leveraging SQL, Python, and Power BI to drive product enhancements, optimize processes, and deliver actionable insights for complex systems. Seeking to transition into advanced product management or data strategy roles where analytical rigor and cross-functional leadership can deliver significant business value.
Product Analyst
Hyderabad, Telangana, India
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Summary
Currently serving as a Product Analyst, driving system enhancements and data-driven product decisions within the reinsurance sector.
Highlights
Collaborated with cross-functional teams to gather requirements, document BRDs/FRDs, and support significant enhancements to the ReNova Reinsurance Administration system.
Performed SQL/Oracle-based data analysis and cleansing, identifying process inefficiencies and delivering actionable insights that directly informed product decisions.
Conducted comprehensive gap analyses between business requirements and system functionalities, enabling accurate resolution strategies and workflow improvements.
Processed and analyzed large volumes of data using Excel, SQL, and Python, developing Power BI dashboards and reports to support critical business reviews and strategic planning.
Managed setup testing and data validation in UAT environments, ensuring full compliance with quality and business standards prior to production migration.
Utilized JIRA to track issues, manage tickets, and oversee the full lifecycle of setups and corrections from initiation through successful implementation.
Internship
Noida, Uttar Pradesh, India
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Summary
Completed an intensive training program focused on Python programming and machine learning fundamentals.
Highlights
Completed a rigorous 3-month training program, mastering the fundamentals of Python programming and machine learning principles.
Gained hands-on experience with key Python libraries including NumPy, Pandas, and Matplotlib for advanced data manipulation and visualization.
Learned and implemented core machine learning algorithms such as linear regression, decision trees, and developed robust model evaluation techniques.
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MBA/PGDM
Business Administration
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B.Tech
Computer Science
Grade: CGPA: 8.68/10
Issued By
HackerRank
Issued By
HackerRank
Issued By
Coursera
Issued By
Internshala
Issued By
Internshala
Issued By
Aptron Solutions
NumPy, Pandas, Matplotlib, Machine Learning, Data Analysis.
Oracle, Data Analysis, ETL, Data Cleansing.
Dashboards, Reports, Business Reviews.
Issue Tracking, Ticket Management, Workflow Management.
BRD/FRD Documentation, Requirements Gathering, Gap Analysis, UAT, Product Decisions.
Random Forest, Linear Regression, Decision Trees, Model Evaluation.
Excel, Spreadsheets, Financial Reporting, Data Processing.
ReNova Application, Insurance.
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Summary
Developed a machine learning model to predict used car prices based on critical factors such as fuel type, kilometers driven, and registration year.