Jan 24 - Current
Pacific Life Insurance

Student Business Analyst

  • Leading analytical project at Pacific Life, analyzing economic indicators to optimize customer targeting and driving product
  • Generating actionable insights through data analysis, aligning with Pacific Life’s strategic goals to enhance revenue growth and
    competitive edge.
May 22 - Sept 22
Wellness Forever Medicare Limited

Digital and IT : Management Intern

Product Category Enhancement:
  • Examined 90,000+ SKUs, spearheading the impulse product category.
  • Secured a 25% surge in sales through data-driven strategies.
Workflow Automation:
  • Pioneered a project for digitalizing workflows, documents, and partnerships.
  • Partnered with SignDesk to accomplish a 50% reduction in turnaround time.
Corporate Microsite Development:
  • Played a key role in the development of a corporate microsite, streamlining onboarding for numerous firms.
  • Efficiently onboarded over a dozen medium and large-scale firms in just one month, resulting in a 40% increase in partnership opportunities.
May 21 - June 21
Phemesoftware Private Limited

Graphic developer

Content Development:

  • Developed and crafted educational content in technical and business domains for the company's e-learning portal.
  • Influenced over 50,000 users, enhancing their learning experiences.

AI-Based Audio Enhancement:

  • Formulated and executed automated AI-based audio samples (text-to-speech) to elevate user engagement.
  • Realized a significant 30% surge in user engagement through this innovative approach.

Market Insights and Product Strategy:

  • Executed a comprehensive survey to scrutinize technological trends among students.
  • Engaged in continual research on emerging trends in the e-learning industry.
May 21 - Sept 21
D Sys Data Solution Private Limited

Technology Consultant and Development Intern

Customer Relationship Cultivation:

  • Fostered robust customer relationships through collaboration with clients and partners, resulting in a substantial 30% boost in customer retention.
  • Delivered continuous assistance and effective problem-solving to clients and internal stakeholders, leading to an impressive 50% increase in customer satisfaction ratings.

Data Availability and Accuracy:

  • Ensured technological precision and accuracy by implementing data request and hygiene management pipelines, achieving a 25% reduction in data errors.
  • Elevated the accessibility and precision of organizational data, yielding a 20% increase in data availability.

Cross-functional Collaboration:

  • Effectively collaborated with cross-functional teams, diminishing project completion time by 15%.
  • Contributed to a 10% upswing in revenue through dedicated efforts and perseverance.
Dec 19 - Jan 20
Esorus Private Limited

Winter Training and Experience Program

Market Analysis and Sales Growth:

  • Utilized analytical skills to scrutinize market trends and customer behavior.
  • Realized a significant 10% boost in sales through insights derived from data analysis.

Product Development and Revenue Generation:

  • Teamed up with a group of 5 to create and successfully launch a new product line.
  • Generated EGP 50,000 in revenue within the initial quarter of the product's launch.

International Presentation and Communication Skills:

  • Engaged in the Indian forum, presenting on the technological environment in India.
  • Addressed an audience of 50 international business professionals during the presentation.

2023 - 2024
University of California, Irvine - The Paul Merage School of Business

Master of Science in Business Analytics

Academic Pursuit: Master of Science in Business Analytics (MSBA) at UCI Paul Merage School of Business, graduating in the Class of 2024 (Graduation : July 2024).

Meritorious Scholarship: Recognized as the recipient of the highest-awarded merit scholarship.

2021 - 2023
SVKM's NMIMS University

Master of Business Administration in Technology Management

Specilization: Business, Intelligence and Analytics, and Marketing.

Academic Excellence: With a GPA 3.8, awarded with Student Ambassador and Dean's List

Skills developed: Management consulting, business analysis, team leadership, strategic planning, technology management, and market analysis.

2018 - 2022
SVKM's NMIMS University, Mumbai

Bachelor of Technology Honors

Specilization: Information Technology, Minored in Data Analytics

Academic Excellence: with a GPA 3.8, awarded with Student Ambassador and Dean's List

Skills developed: Python, R, DBMS, project management, and software development.

2016 - 2018
The Sanskaar Valley School, Bhopal

High School Diploma

Graduation Date: May, 2018

Educational Board: ISC (Indian School Certificate)

Awards: Subject proficiency award in physical education.


Business Problem:

  • Current music recommendation systems struggle with evolving music preferences, often suggesting familiar artists or albums.
  • Consumers face difficulty discovering new songs, limiting the exploration of diverse music genres.

Project Solution:

  • Develop a classification model categorizing songs as Hip Hop or Rock to enhance music recommendation systems.
  • Improve accuracy in suggesting songs aligned with user preferences, overcoming limitations of current recommendation systems.
  • Address the promotional challenges faced by emerging artists by providing a platform for diverse music exposure.

Following Steps and Outcome of the Project:

  1. Dataset Overview:

    • Dataset size: 4802 entries, 10 columns.
    • Detailed column information, including track_id, musical attributes, and genre (Hip Hop or Rock).
  2. Statistical Exploration:

    • Perform descriptive statistics, correlation analysis, and analyze genre distribution for a comprehensive dataset understanding.
    • Key statistical analyses include mean, median, standard deviation, and correlation between attributes.
  3. Model Development and Pre-processing:

    • Initial correlation analysis using Pandas, selecting impactful variables for decision tree and logistic regression models.
    • Pre-processing steps involve normalization, standard scaling, and principal component analysis to enhance model accuracy.
  4. PCA Analysis:

    • Scree plot analysis for intrinsic dimensions determination and cumulative explained variance plot for PCA feature selection.
    • Utilize 6 components for PCA, effectively reducing the dimensionality of training and testing features.
  5. Model Evaluation and Balancing:

    • Identify and address the issue of disproportionate classification of Hip Hop songs as Rock.
    • Assign weights to correct classifications, retrain models, and balance accuracies at 80% for decision tree and 83% for logistic regression.
  6. K-fold Cross-validation:

    • Mitigate overfitting risks using K-fold cross-validation, dividing data into 10 subsets.
    • Accuracies slightly decrease to 75.82% for decision tree and 78.30% for logistic regression, addressing genre classification imbalance.
  7. Future Recommendations:

    • Decision trees and logistic regression models are effective (>75% accuracy) but suggest incorporating more music types like Pop, Country, and R&B.
    • Emphasize the importance of using computer resources wisely, regular model updates, and the potential for a more personalized music recommendation experience.


The “Used Car Price Recommendation” project aims to revolutionize the used car market, recognizing its expansive and dynamic nature. This sector presents significant challenges for both buyers and sellers, primarily due to the absence of a standardized pricing mechanism. This absence leads to uncertainties and discrepancies in transactions, making it difficult for parties involved to determine fair values. 

Following Steps and Outcome of the Project:

  • Exploratory Data Analysis (EDA):
    • Conduct crucial EDA using Seaborn and Matplotlib to understand patterns, distributions, and relationships in the dataset.
    • Visualize key features like brand count, car year distribution, and status count for holistic dataset insights.
  • Machine Learning Model Development:
    • Develop recommendation system using Nearest Neighbors algorithm, converting categorical variables to dummy variables for training.
    • Nearest Neighbors chosen for handling intricate pricing dynamics, trained on preprocessed dataset for accurate personalized price estimates.
  • User Interface with Widgets:
    • Implement interactive ipywidgets-based user interface with dropdowns for easy input of car details.
    • Dynamically update options based on selected brand, ensuring a responsive interface for a user-friendly experience.
  • User Input Processing and Recommendation:
    • Process user input upon button click, convert it for the trained Nearest Neighbors recommendation model.
    • Identify similar cars, calculate median price, and provide the user with an expected price for informed decision-making.

Associated with SVKM’s Narsee Monjee Institute of Management Studies (Graduation Project)

  • A group project focused on developing a chatbot for financial services using artificial intelligence.

  • The chatbot was designed to address multiple domains of the financial sector, with the aim of easing users’ financial activities.

  • Conducted a literature review, user survey, and stakeholder analysis to identify needs and requirements.

  • Experimented with natural language processing approaches, using Huggingface Transformer and TF-IDF vectorizer, and machine learning classification algorithms, with SVM providing the best results.

  • Created sample test questions and different forms of questions to ensure the chatbot caters to various domains of the financial sector.

  • Chatbot was deployed on the Heroku server, making it accessible to users online.

  • aimed to streamline personal finance travel by providing customized information and new research solutions to assist users in making better decisions regarding their financial activities.

Created an analytical dashboard for tracking and visualizing COVID-19 data. This project involved monitoring and analyzing various key parameters related to the virus, including:

  1. Cases by Country: Visualized the distribution of COVID-19 cases across different countries, providing a clear overview of the global impact.
  2. Cases per Country: Presented a comprehensive breakdown of the number of cases in each affected country, aiding in the identification of high-risk areas.
  3. Deaths per Country: Created visual representations of COVID-19-related fatalities in different countries, facilitating a deeper understanding of the global mortality rates.
  4. Total Cases: Generated visualizations illustrating the cumulative number of confirmed COVID-19 cases over time, allowing for trend analysis.
  5. Total Deaths: Developed graphical representations to showcase the progression of total deaths due to COVID-19, aiding in tracking the severity of the pandemic.
  6. Mortality Rate: Calculated and displayed the mortality rate as a percentage, offering insights into the severity of the virus in different regions.
  7. Growth Rate: Visualized the rate of growth in COVID-19 cases, enabling users to assess the speed at which the virus was spreading.
  8. Cases per Day: Created dynamic graphs to track the daily increase in COVID-19 cases, helping stakeholders stay informed about the latest developments.
Case Studies
  • Research Focus:

    • Comprehensive analysis of Reebok in the athletic footwear and apparel industry.
    • Specific emphasis on communication aspects.
  • Comparison with Competitors:

    • Major competitors include Nike, Adidas, Under Armour, and New Balance.
    • Parameters for comparison:
      • Market share.
      • Revenue.
      • Product diversity.
      • Marketing strategies.
      • Digital engagement.
      • Target audience.
      • Brand positioning.
      • Customer satisfaction.
      • Retail presence.
      • Sustainability initiatives.
  • Strategic Recommendations:

    • Enhance communication practices for Reebok.
    • Specific recommendations:
      • Leverage digital marketing.
      • Emphasize sustainability.
      • Implement personalized marketing.
  • Analytical Support:

    • Detailed SWOT and PESTEL analyses.
    • Offer a strategic roadmap for Reebok.
  • Objective of Recommendations:

    • Potentially increase market share and profitability for Reebok.
  • Importance of Continuous Monitoring:

    • Emphasizes the ongoing effectiveness and relevance of Reebok’s communication practices.
    • Highlights the need for continuous monitoring of market trends and competitor strategies in the dynamic industry landscape.
Link: Pricing and Bundling Strategies at Wellness Forever Medicare Limited
  • Case Study Focus:

    • Examines pricing and bundling strategies of Wellness Forever Medicare Limited.
    • Wellness Forever is a prominent pharma retail chain in India with over 200 stores.
  • Insights Provided:

    • Offers insights into Wellness Forever’s approach to:
      • Pricing.
      • Product bundling.
      • Discounts.
  • Impact on Customer Behavior and Sales:

    • Examines how pricing and bundling strategies influence:
      • Customer behavior.
      • Sales performance.
  • Objective of the Case Study:

    • Aims to provide valuable insights and lessons for other retail businesses.
    • Focuses on optimizing their pricing and bundling strategies.
  • Methodology:

    • Analyzes data and strategies used by Wellness Forever Medicare Limited.
Link: Sales pipeline and process at Godrej Interio
  • Company Profile:

    • Godrej Interio: India’s largest furniture brand.
    • Key factors contributing to success: Innovation, diversity, and customer satisfaction.
  • Market Presence:

    • Vast and vibrant product portfolio.
    • Presence in over 430 cities through company-owned stores and dealers.
  • Case Study Focus:

    • Explores how Godrej Interio’s dedication to ergonomics contributes to its leading position in the furniture industry.

Management and Consulting Skills:

  • Marketing Analytics: Proficient in applying analytics to marketing strategies.
  • Consultation: experience in diverse industries, including problem identification, data analysis, and data-driven solution development to optimize business performance.
  • Complex Problem Solving: Proficient in identifying and solving complex business problems through large dataset analysis and predictive modeling.
  • Project Management: Experienced in managing end-to-end projects, from defining project scope to coordinating project teams for successful delivery.
  • Communication Skills: Leadership skills with strong verbal and written communication skills, including the ability to present complex data analysis to non-technical stakeholders and collaborate effectively with cross-functional teams to achieve project objectives.

Technical and Analytical Skills:

  • Programming Languages: Skilled in Python, R, and SQL.
  • Data Analysis and Visualization: Proficient in Microsoft Office, SPSS, Tableau, and Microsoft Power BI, and Alteryx.
  • Statistical Expertise: Strong knowledge of computational statistics, statistical methods, and data management.
  • Data Analytics: Proficient in business intelligence, machine learning, predictive analytics, and organizational behavior for analytical decisions.
  • Information Technology: Knowledgeable in Human-Computer Interaction, software design, requirements engineering, and information retrieval.
Awards & Recognition

Merage MSBA: Merit Scholarship

awarded based on academic and co-curricular excellence

Student Ambassador of NMIMS University

awarded based on academic and co-curricular excellence

NMIMS University: Dean's List

awarded based on academic and co-curricular excellence

Semi Finalist of Chancellor's Challenge,

a 6 month flagship entrepreneurship event by NMIMS University
Licenses & Certificates


  • IBM Data Science Graduate - 2019-2022
  • Runner up – ICE Hackathon  -  Oct 2021 

  • Lean Six Sigma Green Belt (ICGB) - Oct 2021

  • Google Data Analytics Specialization  
  • Data Visualization with Tableau Project (UC Davis)
  • Machine Learning (Stanford)
  • Python Basics (University of Michigan)

  • Developing Credibility as a Leader
  • Emerging Leader Foundations 

  • Intermediate Python 
  • Introduction to Python