• Utilized Python for data cleaning, preprocessing, and exploratory data analysis to derive actionable insights.• Developed interactive dashboards and visual reports using Microsoft Power BI to communicate findings to stakeholders.• Implemented machine learning algorithms, including regression models, to predict and analyze data trends.• Applied linear and logistic regression techniques to model relationships between variables and predict outcomes.• Evaluated model performance using metrics such as R-squared, RMSE, and AUC-ROC.• Created comprehensive reports detailing project progress, findings, and recommendations.

• Extensively employed Python for tasks involving data cleaning, preprocessing, and performing exploratory data analysis (EDA) to derive actionable insights.• Implemented machine learning algorithms, including regression models, to predict and analyze data trends, enhancing decision-making processes.• Applied advanced statistical techniques, such as linear and logistic regression, to model relationships between variables and forecast outcomes accurately.• Evaluated model performance using key metrics like R-squared, RMSE (Root Mean Squared Error), and AUC-ROC (Area Under the Receiver Operating Characteristic Curve) to ensure robust analysis.• Leveraged advanced data visualization techniques with Python libraries like Matplotlib and Seaborn to create insightful visualizations.

• Created dashboards utilizing Pivot Charts and used Slicers to filter the sales data in domains like sales, customer relations, and finance.• Utilized Google forms to gather information about the career goals and learning preferences of Generation Z. • Analysed the collected data and extracted valuable insights through Joins and Aggregate Function in SQL. • Designed interactive dashboards, reports and user interfaces using Excel’s and Power BI’s features.

• Performed data cleaning and preprocessing to ensure high-quality datasets.• Utilized Python libraries such as Pandas, NumPy, and Matplotlib for data manipulation and visualization.• Conducted exploratory data analysis (EDA) to uncover trends, patterns, and insights.• Automated data collection and reporting processes using Python scripts.• Assisted in creating dashboards and reports using visualization tools like Power BI.• Documented data analysis processes and findings for future reference and decision-making.• Assisted in the design and development of data-driven solutions to optimize business operations.

• Responsible for consolidating and analyzing financial data, taking into account company’s goals and financial standing.• Utilize SQL queries to extract, clean, and transform financial data from databases for analysis.• Perform in-depth financial analysis using Microsoft Excel, including financial modeling, forecasting, and variance analysis.• Develop interactive dashboards and reports in Power BI to visualize financial data and key performance indicators (KPIs) for stakeholders.• Create custom ad-hoc reports and financial presentations in Microsoft Excel to communicate insights and recommendations to management.• Collaborate with cross-functional teams to ensure alignment of financial forecasts with business objectives and strategic initiatives.• Perform data validation and reconciliation to ensure consistency between financial systems and reports.• Support FP&A activities by providing insightful analytics and recommendations to improve financial performance and efficiency.• Communicate financial insights and analysis effectively to stakeholders using finance-specific language and terminology.