•Build and maintain scalable data pipelines in both AWS/ADLS utilizing SQL & Python; ensure automatic and efficient data flow between diverse internal and external systems, demonstrating proficiency in ETL processes and large-scale data handling within cloud environments•Leverage technical skills and comprehensive knowledge of SQL and RDBMS structure within data warehouse to swiftly address and articulate complex data insights to non-technical stakeholder queries, enhancing customer satisfaction and streamlining data accessibility•Conduct code reviews with team members and implemented code feedback in a timely and effective manner; kept track of progress and thought process in Jira with story mapping functionality•Troubleshoot, test, and deploy fixes for production issues, collaborating with teammates to ensure data reliability

•Cultivate and deliver weekly teaching plans for 5-6 middle and high school clients in math, ACT/SAT prep, AP Subjects (Statistics, Chemistry, Calculus, CS), Spanish and English; administer 8-12 hours of instruction per week•Catalogue and communicate student progress to track consistency, improvement, and effectiveness of tutoring methods

•Advise peers through 5-10 weekly undergraduate resume and cover letter reviews for jobs and internships, serving as career development role models, and connect students with resources for success in professional endeavors •Utilize communication, advising, and time management skills, while providing constructive criticism in a welcoming and supportive environment•Receive extensive team training and attain access to professional development; recognized by the student affairs team for positive contributions to Duke community

• Partnered with Dr. Cary Moskovitz to explore, quantify, and analyze copyright law and its relation to text recycling in the NSF research grant industry as well as textual structurization of journal articles as well as conduct quantitative research on paper structure • Categorized 100 grants by paper structure into varying IMRAD categories; analyzed variations on structure by paper field and content (empirical, theoretical, computational); reported findings in article published in Journal of Technical Writing and Communcation• Authored code to categorize grants into relevant categories (empirical, computational) with the use of fitz python package • Gathered, organized, extracted, and tailoedr relevant data pertaining to 600 grants for optimal use in R; create and audit excel spreadsheets to maintain database of grant metadata for report and analysis of text recycling• Certified accuracy of 2015 data findings as well as commended for analytical insights and diligence in cleaning and collecting data in “Text recycling in STEM: A text-analytic study of recently published research articles” published in Accountability in Research

•Ensured quality of ESG data streams in centralized AWS S3 data warehouse by utilizing SQL to maintain reliable data infrastructure for future reporting and business needs; adapted code solutions to accomplish business user queries •Developed SQL DML to target DQ investment data issues within Azure SQL Data Warehouse (SQLDW); effectively identified and corrected ingestion process issue in the transformation of the ETL cycle by utilizing validation test cases •Deployed code into Bitbucket to eliminate all future similar issues and ran updated scripts in ADLS to unload code upstream after providing extensive documentation of the DML and validation of its functionality•Conducted code reviews with team members and implemented code feedback in a timely and effective manner; kept track of progress and thought process in Jira with story mapping functionality

• Collaborate with Dr. Xiao Hu to build machine learning models to improve upon MetaMap algorithm that identifies UMLS concepts in clinical notes; pilot and spearhead the translation of research findings to publication • Program and employ NLP techniques (for ex: Word2Vec/BERT embedding and TSNE/UMAP dimension reduction) to construct informative models using logistic regression, random forest, naïve bayes, and SVM algorithms• Utilize TensorFlow, CNTK, Scikit_learn, and Matplotlib to create applicable visualizations and classification models

•Developed and implemented strategies to improve member experience for nonprofit that supplies under-resourced young women with resources to attend college and become financially independent•Created interpersonal skill assessment tools, cataloging student growth over program, composed fundraising speech, and negotiated YouScience™ (career skill assessment tool) subscription free for all students•Piloted peer to peer collaborative program connecting AUM foundation students with Randolph School students to assist with college application progress via self-created personality, career, and interest measurement tools

•Recruited prospective clinical sites, packaged and shipped medical samples to clients, organized FFPE (Formalin-fixed Paraffin-embedded) tumor samples and cataloged product statuses in Salesforce database