It's Umar
I'm a
Turning data into decisions, and AI into action.
I support analysts and teams in solving real-world business challenges using data, AI, and scalable solutions that make an impact.
Turning data into decisions, and AI into action.
I support analysts and teams in solving real-world business challenges using data, AI, and scalable solutions that make an impact.
I'm Umar, a data analyst and business strategist passionate about turning raw data into meaningful insights. With hands-on experience in tools like Python, SQL, Power BI, and Excel, I’ve solved real-world problems across domains like e-commerce, sales, finance, and healthcare. I integrate AI tools like ChatGPT, Claude, Gemini, Deepseek, Julia, Claude, QuadraticHQ and Copilot into my daily workflow to work smarter and faster—whether it’s generating ideas, accelerating reporting, or streamlining code. Earlier in my journey, I strengthened my problem-solving mindset by consistently practicing data structures and algorithms in Java, which helped build my logical foundation. Moreover, Currently I'm upskilling with machine learning and exploring the key essentials of cloud computing (AWS).
Before diving deep into data, I began by exploring frontend web
development—building projects with HTML, CSS, JavaScript, Bootstrap,
and Tailwind. That phase taught me the value of structure, usability,
and design, which now help me create user-friendly dashboards and
reports in analytics.
Since then, I’ve developed full-fledged analytics solutions, automated
ETL processes, built dynamic dashboards, and shared data-driven
recommendations with measurable business impact. I'm deeply curious,
continuously improving, and committed to making a meaningful impact
through data.
-> I may not know everything, but I’m relentless when it comes to
learning, growing, and improving every day.
-> Outside the data world, you’ll often find me exploring new places,
sipping on a warm cup of tea, and staying curious about how technology
continues to reshape our lives.
Built an end-to-end Customer Churn Prediction system using Python (scikit-learn), MySQL, and Power BI. Performed ETL, cleaning, EDA & feature engineering; trained a Random Forest model to predict churners. Integrated predictions into Power BI dashboards enabling data-driven retention strategies and potential 3–8 pp churn reduction.
Retail/wholesale company was struggling with unsold inventory and vendor inefficiencies. I built a full analytics pipeline where I analyzed vendor purchases, sales, inventory & profitability to support strategic purchasing & inventory decisions. (Python, SQL, Power BI)
Utilized SQL, Excel & Power BI. Explored operational data from Ola Cabs to uncover trends related to ride volume, booking status, customer ratings, cancellations, and payment behavior to generate data-driven insights & support in business decision making.
I explored Walmart’s sales data to uncover trends in customer behavior, top-selling products, and peak sales hours. From building a SQL-backed database to creating new features and visual insights, the project answers key questions that help optimize marketing, inventory, and profit strategies.
Solves the problem of manual, fragmented personal finance tracking by centralizing income/expense logs, automating calculations, and providing interactive visual dashboards for better budgeting.
Built a real-time, API-powered Power BI solution to integrate multi-city weather and air-quality data, delivering live KPIs and predictive trends for analysts, students, and operational monitoring..
Developed a real-time Power BI dashboard for a multi-card financial services provider, unifying weekly insights on customer behavior, revenue, and card performance to boost revenue growth, reduce delinquency, and optimize geographic strategies.
Analyze sales trends and customer behavior from a coffee shop dataset. The dashboard highlights peak hours, best-selling products, and revenue trends—helping store owners make smarter decisions on timing, pricing, and product focus.
Delivered a high-level KPI dashboard using synthetic data ( 1K patients, 28K encounters, 48K procedures) to enable MGH leadership to track admissions, insurance coverage, LOS, and financial metrics for strategic decision-making
Target Brazil needed clarity on customer behavior and sales trends. I built a complete analytical solution using SQL, Python, and Power BI by unifying fragmented data, delivering actionable insights on customers, sales, products, and operations to drive strategic decisions.
A dynamic currency converter using HTML, CSS, and JavaScript, leveraging an API to provide real-time exchange rates.
Interactive Tic Tac Toe game implemented with HTML, CSS, and JavaScript for a fun and engaging user experience.
Replica of Amazon.in website created with HTML and CSS, showcasing product listings and a user-friendly interface
Functional calculator application built with HTML, CSS, and JavaScript for basic arithmetic operations.
Python, SQL, Statistics, Reporting
- Focused on Data Analytics and Commercial Insights for the data science team.
- Data Cleaning, Feature Engineering, EDA, Insight Extractions.
- Uplift testing, Statistical Analysis.
- Recommendations and Commercial Reporting
Power BI, MS Excel, EDA
– Performed data analysis on multi-factory operational data to identify equipment failure patterns.
– Built an interactive Power BI dashboard to monitor factory downtime and machine health.
– Used Excel for data classification and transformation & Delivered data-driven insights and to improve manufacturing efficiency.
HTML, CSS, JavaScript
– Worked on front-end projects including portfolio, web application for Numeric Calculation mainly utilizing HTML, CSS, JavaScript for designing & functionality, VS code as code editor, AI tools for brainstorming & debugging
Completed this government-recognized online course with an offline proctored exam, earning Elite + Silver certification by excelling in data wrangling, visualization, and statistical analysis using Python.
Cleared HackerRank SQL (Advanced) Skills Certification, demonstrating proficiency in complex queries, window functions, indexing, pivots, and query optimization in a practical assessment.
By Deeplearning.AI, Stanford University, Coursera. Covered ML foundations & neural networks; detailed study of linear & logistic regression, classification, & all related topics; built predictive & classification models using Python and scikit-learn.
Mentored by Aryan Singh (Google) & Deepanshu Udhwani (ex-MakeMyTrip). Focused on Python, SQL, Excel, Power BI, Prompt engineering and AI tools along with their implementation via projects.
Completed this rigorous course with an offline proctored exam and ranked among the top 1% nation wide. Gained expertise in SQL, ER modeling, relational algebra, normalization, and transaction management.
Python
Python Libraries
MySQL
Power BI
MS Excel
Java
Html
CSS
JavaScript
Bootstrap5
GitHub
Jupyter
ChatGPT
Gemini
Copilot
Claude
Deepseek
QuadraticHQ
Streamlit