Resume

Summary

Data professional with 3+ years’ experience specializing in research, statistics, and data-driven solutions in the social impact space. Passionate about applying statistics, technology, and data science to tackle systemic and societal challenges to create meaningful outcomes.

Hard Skills

• Languages: Python, R, SQL

• Visualization: Tableau, Power BI

• ML: TensorFlow, PyTorch

• Big Data: AWS, Hadoop

• Version Control: GitHub, Bitbucket

• Project Management: Agile, JIRA

Education

Soft Skills

  •      Intellectual Curiosity

  •      Storytelling

  •      Attention to Detail

  •     Problem-Solving

  •      Self-Directed & Team-Oriented

  •      Analytical Expertise

08/2023 – 12/2024 Master of Science in Data Science @ Rice University

08/2019 – 01/2023 BA in Statistical & Data Science, and Psychology @ Smith College

08/2015 – 05/2019 AA in Multidisciplinary Studies @ Houston Community College

Work Experience

  • 06/2025 – Present

    • Streamlined client data collection in Google Workspace to enhance the CEO’s efficiency.

    • Ensured smooth daily operations in client onboarding workflow per CEO’s request.

  • 10/2023 – Present

    • Conducted market research to identify customer data needs and inform POGO’s data collection strategy.

    • Advised on optimal data analytics tools and practices to align with POGO's startup goals.

  • 06/2023 – Present

    • Developed automated Tableau & Power BI dashboards with SQL-based data extraction reducing stakeholder workload by an average of 4 hours per week and accelerating security risk mitigation.

    • Reduced secure data request processing time by 30% by leveraging in-house APIs and open source NLP techniques to develop a Python-based logistic regression model, automating approval/rejection classification.

  • • Supported new introductory data science course at Holyoke Community College, facilitation student learning and comprehension of course materials

    • Aligned course objectives and student needs with supervising professor, enhancing the educational experience for all participants

  • 09/2022 – 01/2023

    • Leveraged the 2017 Global Findex Database to develop a decision tree model that predicts individuals’ access to emergency funds in Sub-Saharan Africa with 68% accuracy.