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Street Address -272-3728 EMAIL AVAILABLE https://LINKEDIN LINK AVAILABLE Open to Relocation EDUCATIONNortheastern University Boston, MAMaster of Science, Data Science (GPA: 4.0) Graduation Date: May Street Address  Relevant Coursework: Database Management, Data Mining, Machine Learning, Data Visualization, Algorithms Boston University Boston, MABachelor of Arts, Mathematics Statistics (GPA: 3.61) Graduation Date: Jan 2021 Relevant Coursework: Data Science in R, Mathematical Statistics, Probability, Python, Database Management in SQL TECHNICAL SKILLSProgramming Languages: SQL (MySQL), Python (Pandas, Scikit-learn), R, SAS Data Analytics: ETL, Tableau, PowerBI, MongoDB, JIRA, GitHub, Microsoft Excel, Google Analytics, Business Analytics Data Science: Machine Learning, A/B Testing, Deep Learning, PyTorch, TensorFlow, NLP, Text Mining, Microsoft Azure Soft Skills: Problem-Solving, Team player, Communication & Collaboration, Innovative mindset, Quick Adaptation PROFESSIONAL EXPERIENCEModel Earth, Data Scientist, Remote Aug 2024  Now Engineered an ETL pipeline with Python for efficient preprocessing and validation of emission data, improving data integrity and boosting processing efficiency by 8%. Simplified data handling for improved analytics. Developed interactive web visualizations of emission data using React.js and HTML, enhanced the user interface with a custom-designed side navigation bar, improving data presentation and site usability. CREWASIS, Data Scientist Intern, New York May 2023  Sep 2023 Project 1: Barbie Financial Performance Analysis using NLP and Machine Learning Modeling Led a group of 4 to build an ETL Pipeline, collected and cleaned 6 GB media text data using Python (nltk), unveiling cost and revenue structures, identified trends in Barbies financial performance, and provided 5+ actionable insights. Collaborated with the marketing team to analyze Barbie's business model, leveraged NLP (LDA) and Exploratory Data Analysis (Pandas, NumPy, Matplotlib, Seaborn, Word Cloud) to decode customer behavior and preferences. Engineered a key performance indicator system and visualized business performance using Python to monitor financial performance and providing data-driven insights to support future resource allocation strategies. Devised targeted marketing strategies and created 10+ Tableau dashboards; presented findings to team lead and showcased on company website, resulting in a 4.3% increase in content engagement. Project 2: Attribution Analysis of Retail Website Membership Decreasing Organized a group of 4, applied the 4P marketing model and conducted an in-depth Attribution Analysis using SQL (MySQL) and Excel to identify and rectify a 12% downturn in retail website membership. Utilized Python for linear regression to identify decisive factors influencing member retention. Analyzed user behavior pathways with Python, employed k-means and DBSCAN clustering to segment users into 5 distinct groups, uncovering characteristics and identifying improvement areas. Conducted funnel analysis to identify low conversion rates from website visits to product views, pinpointing product presentation and recommendation algorithms as key issues. Proposed strategic enhancements based on analysis findings. Delivered 2 detailed presentations to the engineering and marketing teams, resulting in a 7% increase in conversion rates. NACEA, Analyst Intern, Alhambra Jul 2020  Sep 2020 Unveiled revenue growth factors for a travel website during the COVID-19 pandemic by dissecting business models and segmenting revenue, resulting in a 13% increase in quarterly revenue. Visualized KPIs including user growth, conversion rates, and purchase frequency using Python (Matplotlib), identifying a significant increase in new users opting for short-term tours, leading to targeted strategic adjustments. Conducted a user persona analysis and utilized K-Means clustering to identify preferences and price sensitivity, mapped insights to product offerings and resulting in 5+ actionable business strategy adjustments.