Washington DC-Baltimore Area
As a consultant at Everforth ECS, I've transformed data handling by automating reporting workflows and developing data pipelines, which slashed manual efforts significantly. Our team's strategic use of Azure Databricks and NLP models has enhanced dynamic visualization and trend identification, driving key business decisions. I have also helped two dev teams acheive project milestones by being a primary business liaison between stakeholders and team members.Equipped with a bachelor's degree in Computer Science and Data Science from NYU, I bring a rigorous analytical foundation and technical background to the table. My competencies in Python and various data platforms, alongside a talent for leading Agile team sprints, contribute to our mission of delivering insightful data analyses and supporting ECS's clientele in their strategic initiatives.
Serve as the primary liaison between business stakeholders (Product Owners, Department leadership, partner agencies) and technical teams, ensuring that biometric system requirements are fully captured, documented, and translated into actionable development tasks. Elicit, analyze, and prioritize requirements for biometric enrollment, matching, and verification workflows, aligning them with mission objectives, security mandates, and federal compliance standards. Develop process flows, data models, and architectural overviews (e.g., biometric data capture, storage, and exchange) to support both high-level decision-making and technical implementation. Translate complex biometric and identity management concepts into business-friendly terms for stakeholders, while also delivering detailed specifications for developers and testers. Create and manage user stories, epics, and acceptance criteria in Agile tools (e.g., Jira, Confluence) to drive sprint planning and ensure successful delivery of biometric features. Validate system functionality through hands-on testing (e.g., XML data exchanges, API calls, biometric record formats), ensuring accuracy, interoperability, and compliance with standards like NIST and ISO. Support change management by analyzing legacy requirements and aligning them to new biometric solutions that enhance scalability, performance, and security. Supported User Acceptance Testing efforts on deliverables during parallel operations roll-out to gauge readiness for future releases. Provide continuous feedback to leadership on project progress, risks, and outcomes, ensuring biometric initiatives meet operational goals and interagency collaboration needs. Created Power BI/Power Apps dashboards to support internal project process and analytics needs.
• Tech consultant for VA’s Veteran’s Experience Office Contact Center (VEOCC), collaborating with a 4-person team to analyze call center data, build automated Azure pipelines, and develop Power BI/Apps dashboards. • Applied NLP (Python’s regex, NLTK) to analyze unstructured Salesforce call data, identifying veteran inquiry trends. Delivered insights to VA leadership, impacting decisions for 16.2M veterans. • Created predictive ML models (scikit-learn) forecasting call volumes for proactive resource management. Used unsupervised clustering to conduct topical analysis on veteran concerns. • Conducted exploratory data analysis (EDA) with Python and SQL on 10M+ data rows, uncovering key insights. Automated validation scripts in GitHub, improving data integrity. • Automated reporting workflows in Azure Databricks, reducing manual reporting by 90%, enhancing strategic insights. • Built Azure pipelines to ingest data into Blob Storage, performing ETL in Databricks with Python. Leveraged Azure Data Factory to automate data flow into Databricks’ Medallion Lakehouse, saving 40 weekly hours of manual work. • Led Agile sprint planning, improving task efficiency by up to 75% and reducing rollover by 30%. • Conducted code reviews ensuring quality, security, and reliable deployment in GitHub production environments. • Managed 4 Power BI/Apps dashboards for two government enterprises, delivering MVP solutions and gathering enhancement requirements.
Interned at Emerson Collective through a child organization, Get Food USA, which was a non-profit founded in response to the ongoing Covid-19 pandemic. Used Python to create informative data visualizations, and assist my team in finding the right questions to ask when working with data. For example, my team sought to increase youth volunteer engagement in their logistics program, so I helped brainstorm some data-driven ideas and incentives to seek out more youth engagement.
Part-time summer position as a Stern EMBA program Office Assistant at New York University’s satellite campus in Washington D.C. Helped with various logistical tasks and conducted various administrative work.
Interned at the Japan-America Society of Washington DC, assisting in event planning for the annual National Japan Bowl, a popular East-coast Japanese language and culture competition for high school students located across the Americas and Asia-Pacific. Assisted event organizers with logistical planning, volunteer recruitment and training, and marketing materials for Washington D.C's annual National Cherry Blossom Street Festival.