Data Entry

NISHI PRIYANKA HEMBROM

+91-620******* •***************@*****.*** •www.linkedin.com/in/nishi-priyanka-hembrom-783248230 •https://github.com/NishiHembrom SUMMARY

A versatile and results-oriented IT professional with an engineering degree in Computer Science from Parul Institute of Engineering & Technology. Skill Set Includes Data Analytics, Business Intelligence, and Cloud Technologies. Expertise and experience in Power BI, Azure, Power Platform, and Microsoft Dynamics 365 for decision-making based on data. Requirement gathering, business analysis, leading cross-functional teams, and delivering world-class deliverables in the form of insights and reports align with organizational objectives. These targets optimize processes, Onshore operational capabilities, and support strategic business initiatives. EDUCATION

B.Tech, Computer Science & Engineering June 2026

Parul Institute of Engineering & Technology 6.40 CGPA Vadodara, Gujarat

Relevant Coursework: Big Data, Cloud Computing, AI, ML, IoT, Software Testing, Web Development 12th Science Stream July 2021

Sri Chaitanya Techno School 72 percent

Visakhapatnam, Andhra Pradesh

Relevant Coursework: Physics, Chemistry, Maths

10th April 2018

S J DAV Public School 71 percent

Chaibasa, Jharkhand

Relevant Coursework: Science, Maths

TECHNICAL SKILLS

Programming & Data Analysis: Python, R, SQL, JavaScript, HTML, CSS Data & BI Tools: Power, Microsoft Dynamics 365, Excel Databases & Cloud Platform: SQL Server, MongoDB, Azure NoSQL Databases Developer & Collaboration: Git, GitHub, APIs, including OpenAI, Gemin npm Framework & Libraries:Node.js, Express.js,React.js, Bootstrap DevOps and Lifecycle: Knowledge of SDLC phases, continuous integration, and prioritization in analytics projects AI & GenAI: Optimization of NLP model and AI performance for data-driven insights ACADEMIC PROJECTS

•T20 Cricket World Cup Data-Analysis

Implemented an all-encompassing ETL data pipeline implementation for web scraping using JavaScript and efficient data cleaning, structuring, and manipulation of reusable scripts using Python Pandas. Advanced data transformation and normalization methods had been carried out to reshape and process raw JSON data into a structured relational dataset (e.g., dim_match_summary, fact_batting_summary), thereby maintaining the integrity of the data so that a valid depth-level purpose of statistical analysis and concerning evaluation of the teams and players might take place.

•Revenue Analytics: Hospitality Domain

Implemented a revenue analytics project for hospitality using Python and the Pandas library for heavy-duty cleaning and transformation of data.

Key revenue insights were generated from the cleaned and transformed data, which, when implemented, can improve performance in the hospitality sector.

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