About
Highly accomplished Data Analyst with 4+ years of experience leveraging advanced statistical methodologies and multi-source data integration to drive impactful business outcomes. Proven expertise in architecting and deploying production-grade AI solutions, optimizing ETL pipelines, and developing robust analytical frameworks that enhance data accessibility, reduce processing times, and deliver actionable insights for strategic decision-making. Adept at cross-functional collaboration and translating complex data into clear, quantifiable results.
Work
JerseyStem
|Data Analyst
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Summary
Directed critical data migration and pipeline automation initiatives, enhancing data accessibility and integrity while delivering real-time business intelligence solutions.
Highlights
Directed the migration and normalization of organizational records from Excel to PostgreSQL, significantly enhancing data accessibility and integrity for analytical research.
Automated data validation, backup, and ETL processes using SQL scripts and Google Cloud Platform tools, reducing manual entry errors by 50% and accelerating processing time by 40%.
Created interactive dashboards with advanced data visualization tools to deliver real-time insights across 8 key operational metrics, transforming complex datasets into actionable business intelligence.
Documented comprehensive data definitions and reporting methodologies, standardizing data extraction and transformation practices to support effective collaboration.
Cortracker360
|Data Analyst
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Summary
Led the development and deployment of advanced AI and data science solutions, optimizing data processing and enhancing analytical capabilities for over 10,000 monthly users.
Highlights
Architected and deployed a production-grade generative AI chatbot using LangChain and SentenceTransformers, improving model accuracy by 22% and serving 10,000+ monthly users.
Designed and implemented comprehensive data science pipelines for processing unstructured text, incorporating custom cleaning, normalization, and entity extraction techniques.
Refined experimental design and cross-validation strategies within Retrieval-Augmented Generation (RAG) architectures, achieving sub-second latency for 95% of queries.
Automated ETL workflows and established robust data governance protocols, ensuring scalable, high-integrity data processing and supporting real-time machine learning pipeline automation.
Collaborated with product and engineering teams to translate operational requirements into effective data models and technical documentation, reinforcing data extraction methods.
Amazon Development Center
|Analytics Specialist (Transportation)
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Summary
Engineered data automation tools and developed real-time analytics solutions for transportation and logistics, significantly improving operational efficiency and on-time delivery performance.
Highlights
Engineered automation tools using Python and Selenium to streamline case management workflows, reducing daily workload by 4 hours and modernizing ETL processes.
Analyzed over 10TB/day of transportation and logistics data using PostgreSQL and Redshift, applying advanced indexing strategies to reduce query times by 30%.
Developed real-time monitoring dashboards using Amazon QuickSight to track 17 KPIs related to capacity planning, SLA adherence, and incident response.
Coordinated cross-functional operations across fulfillment centers, delivery hubs, and carriers, leveraging rigorous data analysis to resolve delivery disruptions and maintain a 96% on-time delivery performance.
Education
State University of New York at Buffalo
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M.S
Data Science Engineering
Awards
McKinsey Forward Program Graduate
Awarded By
McKinsey
Completed a competitive 10-week digital leadership and strategy development program, delivering actionable recommendations for a global client. Demonstrated significant improvement in agile project management, stakeholder engagement, and data-driven decision-making within a structured business environment.
Skills
Data Science Tools & Technologies
Python, R, SQL, pandas, scikit-learn, spaCy, NLTK, PostgreSQL, Google Cloud Platform, SQLAlchemy, Tableau, Power BI, PyTorch, SAS, SPSS, LangChain, SentenceTransformers, Amazon Redshift, Amazon QuickSight, Selenium, AI/ML Frameworks, Cloud Platforms.
Data Engineering & Analytics Competencies
Data Integration, ETL Pipeline Development, Data Preprocessing, Data Cleaning, Statistical Modeling, Machine Learning, Hypothesis Testing, Predictive Modeling, Hypothesis-Driven Research, Exploratory Data Analysis, Reproducible Research Practices, Statistical Significance Testing, Data Modeling, Generative AI, Model Evaluation.
Professional Practices & Compliance
Interdisciplinary Collaboration, Technical Documentation, Ethics and Compliance, Sensitive Data Handling, HIPAA, Electronic Health Data, Research Design, Biostatistics, Agile Project Management, Stakeholder Engagement, Data-Driven Decision-Making.