Data Science with 1+ years in Data Analysis & Market Research
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Data-driven and detail-oriented professional with experience in data analysis, market research, and creating easy-to-understand reports and dashboards. Skilled in using Python, SQL, and Power BI to analyze data and turn it into useful business insights that support better decision-making. Experienced in customer segmentation, demographic analysis, and identifying market trends to understand customer needs and business opportunities. Able to present complex data in a simple and visually appealing way for managers and stakeholders.
Indian Institute of Technology, Bombay
MS Research · Mechanical Engineering
June 1, 2021 – August 1, 2023
National Institute of Technology, Warangal
Master of science · Applied Mathematics
June 1, 2017 – May 1, 2019
Institute For Excellence in Higher Education, Bhopal
Bachelor of science · Mathematics and Diploma in statistical Analysis
June 1, 2013 – May 1, 2016
AIITECH IT Education
Chief Academic Officer
March 1, 2025 – Present
Dubai, Dubai, United Arab Emirates
Amazon
Sales & Customer Segmentation Analysis
February 1, 2024 – March 1, 2024
India
Indian Institute of space science and technology
Research Assistant
January 1, 2023 – December 1, 2023
Thiruvananthapuram, Kerala, India
Institute For Excellence in Higher Education
Data Analysis & Research Intern
June 1, 2015 – July 1, 2015
Bhopal, Madhya Pradesh, India
K-12 School Analytics & Enrollment Optimization Dashboard
March 1, 2025 – April 1, 2025
Engineered an end-to-end analytics solution using an uncleaned school dataset, performing rigorous data cleaning, missing value handling, and structural preprocessing in Python (Jupyter Notebook). Conducted a comprehensive Student Demographic Analysis and Enquiry-to-Enrollment Conversion Analysis to identify key friction points in the admission pipeline and regional demand drivers. Developed a Drive Time & Commute Analysis (Time Travel) to map student density against transit times, enabling localized targeting and optimization for school transport/logistics. Built interactive Power BI dashboards equipped with predictive modeling to forecast future enrollment trends and empower executive leadership with data-driven decision-making tools.
Coffee Quality Dashboard
May 1, 2024 – June 1, 2024
Built an interactive Power BI dashboard that streamlined data modeling and data cleaning, reducing preparation time by 25% and boosting overall data accuracy by 15%. Enhanced strategic decision-making accuracy by 30% and accelerated data trend identification times by 40% for the client organization.
Laptop Price Predictive Modeling
April 1, 2024 – May 1, 2024
Developed an end-to-end regression model utilizing Scikit-Learn to forecast product pricing, achieving a high-accuracy R-squared score of 0.89. Applied advanced feature engineering and hyperparameter tuning to ensure robust, validated model performance. Utilized Python, Pandas, NumPy, Scikit-Learn, Matplotlib, and Seaborn for data analysis and visualization.
Machine Learning
Stanford University (Coursera)
June 1, 2026 – Present
Certificate in Data Science
Odin School
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse educational background (IIT Bombay, NIT Warangal) and experience across research, education, and industry (Amazon internship) suggest adaptability and a broad perspective. Their involvement in projects like 'K-12 School Analytics' and 'Coffee Quality Dashboard' indicates an interest in applying data science to various domains. The Chief Academic Officer role highlights a commitment to education and mentorship, which can be a positive cultural asset. The breadth of skills and project types aligns well with a dynamic data science environment.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership and communication skills through their Chief Academic Officer role, where they mentored teams and translated technical insights for stakeholders. Their project descriptions indicate an ability to work on end-to-end solutions and present findings clearly. The use of Pyrus and GitHub suggests familiarity with project management and version control, indicating good operational fit for structured data science workflows.