Welcome to my portfolio website. Here you can find my projects and learn more about my skills.
I'm a Data Analyst with 5+ years of experience applying analytics across healthcare, finance, and business operations. Skilled in SQL, Python, Power BI, and Excel, I specialize in transforming messy datasets into clear, actionable insights for decision-making and operational improvement.
My path into analytics is grounded in real-world execution — from supporting a $50M Medicaid billing project as a Business Analyst to launching a culinary business where I used data-driven forecasting to reduce waste by 20% and increase profit margins. This background helps me connect technical analysis with measurable business impact.
I'm experienced in:
I recently completed MIT Professional Education – Applied Data Science and am building skills in predictive analytics and machine learning through hands-on projects including fraud detection pipelines and computer vision models. My code and project write-ups are fully documented for reproducibility and business interpretation.
If you're looking for an analyst who combines technical depth with business understanding — and is actively growing toward advanced analytics — let's connect.
Professional qualifications that validate my expertise
Issued by Coursera
September 2024
Issued by Microsost
April 2024
A Power BI workforce analytics dashboard (Edureka certification project) analyzing 546K+ HR records to uncover retention risk patterns. Built with advanced DAX measures, row-level security for 6 regional roles, interactive filtering, and demographic segmentation, revealing that 73% of new hires are under 30 yet this age group shows highest separation volumes—enabling targeted retention strategies.
Power BI sales analytics dashboard analyzing 51K+ transactions totaling $62.3M across global markets (Edureka certification project). Implemented row-level security for Africa and Europe regional roles and DAX profit calculations. Revealed 23.8% average annual growth (2012-2015) alongside critical profitability challenges: overall 2.4% profit ratio with Central Asia operating at -9.4% loss, while Technology category drives 38% of revenue.
Conducted comprehensive data analysis on FoodHub's order dataset using Python (pandas, matplotlib, seaborn), examining 1,898 orders to identify key trends in restaurant popularity, cuisine preferences, delivery times, and customer ratings, ultimately providing strategic recommendations to improve revenue and customer experience.
Power BI dashboard analyzing Northwind database (2,155 order details, 830 orders) with advanced time intelligence DAX measures (Edureka certification). Revealed 80% year-over-year sales growth alongside critical customer concentration risk: top 3 customers represent 25.6% of $1.35M revenue, with Horst Kloss alone driving 8.7%. Features cascading filters, drill-through pages, and Q&A natural language interface for ad-hoc analysis.
Power BI dashboard analyzing 5,806 Netflix titles (Edureka certification project). Built using Power Query transformations and DAX measures to visualize content distribution, genre mix, and global availability. Shows platform is 65% movies vs. 35% TV shows, with shows averaging 13% higher IMDB ratings despite lower production volume.
mopammu@gmail.com
Laurel, MD
linkedin.com/in/mohitpammu
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