Siri Malatesh Kademani

Data analyst with a strong background in business intelligence, data visualization, and data mining. Proficient in SQL, Python, Tableau, and Qlik Sense. Experienced in data modeling, data governance, analytics, and generating insights. Certified in Tableau Desktop and SnowPro Core [Snowflake].

With nearly 4 years of experience in data analysis and a recently completed MS in Business Analytics from Arizona State University with distinction, I am confident in my ability to contribute to the success of the company. I also worked on various projects in the field of Consulting, Retail, Finance, and public safety technology.

Throughout my academic and professional journey, I have cultivated a strong foundation in data processing, data science, business intelligence, and insight retrieval.

My coursework and practical experience have equipped me with a comprehensive understanding of enterprise analytics, marketing analytics, descriptive and predictive analysis using machine learning, and natural language processing. I am proficient in utilizing tools & languages such as Dimensional Modeling, SQL, Python, Snowflake, Alation, JIRA, Microsoft Office, Tableau, and Qlik Sense.

I am also Tableau Desktop Certified and SnowPro Core Certified.

I believe that my background in data analysis, coupled with my passion for leveraging data to drive strategic decision-making, makes me an ideal fit for the role.

Thank you for your time and consideration.

Sincerely,

Siri Kademani

MS in Business Analytics from ASU.

Coursework: Enterprise analytics, Marketing Analytics, Lean Six Sigma, Quality Management, Descriptive and predictive analysis using ML, Natural Language processing, Deep Learning, Analytical Decision Making, Statistics.

PROJECT EXPERIENCE

• Analysis on Violence against Women: Built 2 Tableau dashboards to analyze root causes for violence against women data across world.
• Interpreted University Medical Insurance Database schema into Entity Relationship diagram.
• Restaurant Revenue Prediction, ASU: Implemented Random Forest, Decision Tree and XGBoost regressor and ensemble stacked model, after preprocessing dataset of 1 lakh instances to annual sales revenue of restaurants based on KPIs.
• Market Analysis for Zomato's Expansion to the US: Propounded market-entry methods for expansion of Zomato in USA by conducting market analysis using data from competitors. Employed techniques like scraping Reddit data with PRAW library, data pre-processing, and LDA modeling. Identified topics such as delivery speed, customer service, and app features to devise launch strategy.
• Parking lot space detection counter: Built a model using Computer Vision for image classification of parking lots by plotting bounding boxes around the cars.