Dynamic and versatile professional with a unique fusion of sales expertise, data science acumen, and software engineering skills. Together, these competencies enable me to communicate effectively, solve complex problems, and drive process improvements, adding lasting value to any team or project.
β’ Gained proficiency with Python, machine learning (supervised and unsupervised), AI, natural language processing, neural networks (deep learning), and data analysis/visualization with SQL, Git, NumPy, Pandas, Matplotlib, Seaborn, and Scikit-learn.
β’ Designed and implemented machine learning models for predicting housing sales prices and loan default likelihood, achieving up to 80-98% accuracy.
β’ Applied Pandas and NumPy skills to navigate, extract, parse, clean, analyze, and visualize data from diverse sources.
β’ Utilized Python libraries Matplotlib and Seaborn to effectively plot and visualize data.
β’ Demonstrated a rapid ability to learn and apply new technologies and statistical methodologies.
β’ Pioneered an advanced communication system for real-time user messaging, enhancing user interaction and system responsiveness.
β’ Architected and deployed scalable microservices in Go, seamlessly integrating with technologies like Kafka, MongoDB, and Amazon SQS for efficient data processing.
β’ Anchored the software development life cycle, adhering to SAFE-Agile methodologies to ensure timely and quality delivery.
β’ Spearheaded comprehensive testing through unit tests, functional tests, and automation, achieving reduced error rates and enhanced system reliability.
β’ Optimized development workflows by leveraging Jira and GitHub, resulting in a 20% improvement in project timelines and collaborative efficiency.
β’ Utilized machine learning techniques and quantitative analysis to devise data-driven pricing strategies, boosting investor return by over 22%.
β’ Tracked and analyzed key performance indicators (KPIs) such as inventory absorption rates, acquisition costs, and projected sales prices, enabling data-driven decision-making and revenue optimization.
β’ Created market reports, financial analyses, and presentations to effectively communicate findings to stakeholders, investors, and team leadership.
β’ Collaborated cross-functionally with sales professionals, finance teams, design teams, and renovation teams to execute tailored initiatives aligned with shared objectives.
β’ Displayed strong project management skills, leading teams to successfully implement individualized strategies and initiatives.