My expertise in Python was key to transforming fragmented, real-world data into actionable business results. For a major US logistics client, I built custom Python scripts to clean and consolidate more than 100,000 delivery records scattered across dozens of Excel and CSV files. Leveraging advanced data wrangling, feature engineering, and integration with Power BI, I uncovered low-profit routes and optimization opportunities that helped the company save over $50,000 a year. This hands-on experience enabled me to deliver robust ETL pipelines, predictive models, and automated workflows for both logistics and academic projects.

I routinely rely on SQL to turn raw, multi-source datasets into reliable foundations for analytics and machine learning. When working with a Canadian marketing agency, I designed and executed complex SQL queries to aggregate, join, and score client and campaign data—driving the deployment of real-time lead scoring dashboards. My SQL skills have empowered executives and stakeholders to access the insights they need, supporting fast-paced client acquisition and strategic business decisions across sectors.

Building interactive, insight-driven dashboards is at the heart of my analytics work. I have created KPI-aligned dashboards in both Power BI and Tableau, helping clients—from NYU professors to logistics executives—visualize complex trends, measure performance, and communicate value to decision-makers. My dashboards have been used to secure promotions, guide policy changes, and track results in real time, blending technical rigor with an intuitive, user-friendly experience.

My journey with Excel began over a decade ago and has evolved into advanced, project-critical applications. I have used Excel for everything from quick-turnaround reporting to building dynamic models and automated analyses. In my logistics and marketing projects, Excel was essential for rapid prototyping, data validation, and creating shareable, client-ready deliverables. Combining PivotTables, VBA, and modern integration with other tools, I’ve repeatedly cut manual work and improved reporting quality for my clients.

A solid EDA foundation underpins every impactful project I’ve delivered. Whether tackling student survey data for NYU or churn datasets for telecom clients, I use EDA to uncover trends, spot outliers, and identify what truly drives results. This approach has allowed me to go beyond surface metrics—delivering actionable recommendations that have led to salary increases, improved client retention, and sharper marketing campaigns.

Applying machine learning to real-world business problems is a growing part of my practice. I have built and deployed predictive models using scikit-learn and XGBoost to guide executive decisions in logistics, marketing, and education. My feature engineering, model evaluation, and scenario simulations have helped organizations optimize customer selection, forecast risk, and fine-tune pricing—delivering measurable ROI and a strategic edge.

My academic background in engineering and Bayesian statistics has proven invaluable for high-uncertainty, high-impact projects. I have used Bayesian state estimation and advanced statistical methods to optimize bioprocess efficiency, improve predictive accuracy, and reduce the need for expensive instrumentation. These techniques help me deliver robust, data-driven solutions in environments where precision and reliability are critical.

Clear communication with diverse stakeholders is central to my consulting approach. I routinely translate technical findings into strategic recommendations for executives, professors, marketers, and engineers—ensuring everyone understands and can act on the insights. Through consultative workshops, data storytelling, and tailored dashboards, I empower non-technical clients to embrace analytics, act on data, and realize business value.

I have designed and implemented scalable, GDPR-compliant data pipelines using Python, SQL, and cloud tools such as Azure Data Factory and Airflow. These pipelines power real-time analytics and dashboarding for smart city initiatives, logistics, and marketing. My data engineering work ensures that complex, messy data is transformed into a trusted, high-value asset ready for decision support and advanced analytics.