Currently a Cybersecurity Risk Specialist at the world's largest retailer, I bring a strong background in risk management, data science, governance, risk, and compliance.
With expertise in cybersecurity governance, risk, and compliance, strategy, data analytics, and quantitative risk management, I help organizations make informed decisions to strengthen their security posture and drive impactful business outcomes. My experience spans working with IT, OT, SOC, IR, and compliance teams to safeguard sensitive data and ensure regulatory adherence through holistic risk management approaches.
Additionally, I have a deep understanding of SDLC, web application development, and data-driven risk analytics. Passionate about leveraging data-driven insights, cybersecurity domain expertise, and strategic risk frameworks, I thrive in dynamic environments that challenge me to innovate and optimize cybersecurity resilience.
Analysis of an advertisement dataset with multi-channel ad spending and their effect on sales revenue using Multiple Linear Regression. Tools Used: Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn)
Analysis of a large set of HR data on Kaggle.com by Faisal Qureshi to understand correlation and create a prediction model for response variable for 'Employee Satisfaction Level' in relation to given predictors. Statistical analysis was performed through Multiple Linear Regression with R programming in Kaggle Notebooks using R Markup.
Analysis of death in the titanic disaster in 1912, as a part of Kaggle competition to predict the likelihood of death of a passenger given background information. Tools Used: Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn)
A visualization project on global CO2 emissions data. The analysis was performed visually on Tableau using publicly available dataset.
A sales metrics dashboard created in Excel. This project utilizes various Excel features such as XLOOKUP, SUM, AVERAGE, MIN, MAX etc. Analysis is performed using Pivot Tables and visualized with pivot charts in an interactive dashboard.
Kaggle is a data science community and platform that hosts competitions, provides datasets, and offers a collaborative environment for machine learning enthusiasts to solve real-world problems and showcase their skills.
Data.gov is a centralized online repository that provides access to a vast collection of government datasets, empowering users to explore, analyze, and utilize valuable public data for research, decision-making, and fostering transparency in governance.
Google Datasets Search is a search engine designed to help researchers and data scientists discover and access a wide range of publicly available datasets. It indexes datasets from various domains and provides metadata information, facilitating efficient data exploration, analysis, and collaboration in the pursuit of knowledge and insights.