Resume

Check My Resume

Education

MASTER of BUSINESS ADMINISTRATION DEGREE: Marketing

2023 - 2024

Saint Peter's University (Jersey City, New Jersey)

MASTER of SCIENCE DEGREE: Data Science

2020 - 2022

Saint Peter's University (Jersey City, New Jersey)

BACHELOR of SCIENCE DEGREE: Mathematics & Applied Physics Minor in Computer Science

2013 - 2017

Linfield University (McMinnville, Oregon)

Research Assistant

March 2024 - May 2024

Saint Peter's University, Jersey City, NJ

  • EV Market Analysis and Consumer Behavior:
    • Developed predictive models for analyzing consumer behavior regarding electric vehicles (EVs), achieving an 89% accuracy in sentiment analysis.
    • Automated data retrieval and processing from YouTube to conduct extensive sentiment analysis.
    • Created a YouTube comment analyzer tool using Selenium and the YouTube API to collect and analyze comments on EV-related videos, incorporating advanced machine learning models for summarization and sentiment aggregation.
    • Increased data processing efficiency by 35% using Apache Spark.
  • EV Vehicle Telematics and Performance Monitoring:
    • Analyzed 100,000+ telematics data points to improve model prediction accuracy by 20%.
    • Deployed machine learning models in Azure Databricks for real-time monitoring simulations of EV performance.
    • Integrated vector database technology to implement similarity search, improving retrieval speed by 40%.
  • EV Energy Informatics:
    • Designed predictive models to forecast energy consumption, improving accuracy by 20%.
    • Conducted grid integration analysis to assess the impact of EV charging on power grids, proposing strategies for load balancing and demand response, reducing energy waste.
    • Led charging infrastructure planning efforts by analyzing geographic, demographic, and traffic data to anticipate future infrastructure needs.

Research Practicum - Visual Search Engine PoC

2020 - 2021

Saint Peter's University, Jersey City, New Jersey

  • Applied cutting-edge techniques in content-based image retrieval using state-of-the-art machine learning and deep learning algorithms to create a visual search engine.
  • Designed, developed, and optimized a deep learning Convolutional Neural Network (CNN) model using the VGG16 architecture in TensorFlow/Keras to power a visual search engine Proof of Concept (PoC).
  • The PoC allowed users to search for similar images to a given query image, and the CNN model was the backbone of the search algorithm.
  • To improve accuracy, transfer learning techniques were employed, leveraging pre-trained models and fine-tuning the last few layers for the specific use case.
  • Conducted extensive data preprocessing and feature engineering to prepare a large image dataset for use in training and validation of the CNN model.
  • Various techniques were used to extract relevant features from the images, such as color histograms, edge detection, and texture analysis.

Research Assistant - Computational modeling of self-organized critical systems

2016 - 2017

Linfield College Department of Physics, McMinnville, Oregon

  • Designed and programmed a mathematical model in MATLAB simulating a fly swarm as the complex dynamic system.
  • Data on the trajectories of the flies was collected and analyzed in MS Excel using VBA.
  • Utilized mathematical properties such as scale invariance and nontrivial power law correlations over factors like time associated with systems exhibiting self-organized criticality to define and understand complex and dynamic systems, including fly swarms.

Research Assistant - Design and building of an autonomous ground vehicle for the IGVC competition.

2015 - 2016

Linfield College Department of Physics, McMinnville, Oregon

  • Conducted research studies leading to the development of an autonomous vehicle and identified and solved electronic design problems, resulting in efficient and cost-effective products.
  • Established compatibility with third party software products through the development of programs for mechanical structure modification and integration.
  • Used OpenCV library and tools (in C++ with CUDA for improve performance) to incorporate real-time optimized Computer Vision (implemented as binocular vision for depth perception).

Work Experience

Freelance Developer - Data Engineer

October 2023 - Present

NHANES pyTOOL API Development and Publishing, Jersey City, New Jersey

  • Developed the NHANES pyTOOL API, an advanced Python library designed to transform access to and analysis of National Health and Nutrition Examination Survey (NHANES) datasets, enabling researchers, data scientists, and healthcare professionals to engage with large-scale, complex healthcare data.
  • Simplified Data Exploration & Retrieval:
    • Engineered a user-friendly interface that reduced data retrieval time by 60%, enhancing efficiency in exploring complex datasets.
    • Enabled seamless access to over 10,000 variables across multiple NHANES survey cycles, allowing for detailed exploration of public health data and insights.
  • Enhanced Research Capabilities:
    • Automated data categorization, cycle year retrieval, and extraction of detailed variable tables to streamline data access and exploration.
    • Developed intelligent file joining mechanisms based on common variables to provide comprehensive and integrated datasets, crucial for advanced analysis and insights.
  • Advanced Data Management:
    • Designed intuitive methods for effortless dataset retrieval and implemented sophisticated filtering and selection techniques to ensure data consistency and integrity across multiple NHANES cycles.
  • Documentation & Community Engagement:
    • Developed comprehensive, user-friendly API documentation that supports diverse user needs, ranging from researchers to healthcare professionals.
    • Established guidelines for contributions and issue reporting to foster community collaboration and continuous improvement.
  • Project Impact:
    • Democratized access to critical public health datasets, reducing barriers to NHANES data analysis and enabling diverse groups to engage with public health and epidemiology research.
    • Advanced reproducible research in public health, providing a foundation for the development of predictive models that can drive meaningful healthcare innovations.

Freelance Data Business Analyst

May, 2023 - Present

E-Scripts Platform and Pharmacy Business Plan – Strategic Data Analytics & Operational Planning, Jersey City, New Jersey

  • Developed an end-to-end platform facilitating secure, electronic prescription management for doctors, pharmacists, and patients, leveraging advanced technologies to enhance operational efficiency and user experience.
  • Conducted comprehensive market analysis, including demand forecasting, segmentation, and competitive analysis, to identify key market opportunities for the pharmacy sector.
  • Built predictive financial models and business case proposals, enabling informed strategic decisions:
    • Break-Even Analysis: Identified optimal sales thresholds for profitability.
    • Cash Flow Management: Designed monthly and annual forecasts to ensure sustained liquidity and financial health.
    • Pro Forma Statements: Projected revenues and operational costs to evaluate long-term growth potential.
  • Engineered a data-driven marketing and operational strategy:
    • Leveraged SQL and Tableau to generate insights on customer buying patterns and inventory needs.
    • Recommended pricing strategies that balanced affordability and profitability.
    • Designed frameworks for customer loyalty programs and community outreach initiatives to drive engagement and retention.
  • Developed operational risk frameworks to address financial, market, and regulatory challenges, ensuring compliance and sustainability.

Data Scientist

Oct, 2022 - Apr, 2023

Modjoul, Inc., Greenville, South Carolina

  • Managing the complete life cycle of Machine Learning products which includes:
    • Data Collection and Data Cleaning.
    • Data Engineering and Feature Engineering.
    • Data Analytics.
    • Building Machine Learning Models and Deployment of Models.
  • Data Engineering and Cloud Services:
    • Collected, cleaned, and manipulated raw data using both SQL and NoSQL databases.
    • Leveraged cloud-based infrastructure, specifically AWS, to drive the development of machine learning models.
    • Designed and implemented secure AWS pipeline architectures for multi-tenant Data Processing Analytics and Visualization, and batch data payload processing based on batch size and time intervals.
  • Collaboration and Data Management:
    • Collaborated with cross-functional teams to deliver data-driven projects while ensuring data security and privacy compliance.
    • Conducted research on new technologies and best practices for data management and processing, such as MLOps and DataOps.
    • Designed, created, and administered a collaborative environment using AWS's Amazon SageMaker Studio and a centralized data repository, a Data Lake created using AWS's Lake Formation

Intern - Analyst, Data & Analytics

Jan, 2022 - May, 2022

Digitas Health, New York, New York

  • Part of a team that created Business Vitals Dashboard PoC MVP for Tracking and Monitoring business vital information.
  • Integrated data from multiple tools into one centralized data resource for simplicity, visibility, and flexibility, together with data visualization, eliminating the need for specialized expertise or support resources for the End User.
  • Collaborated with stakeholders and tech teams to ensure solution aligned with business and technical requirements.
  • PowerBI platform was used to create the Business Vitals Dashboard POC MVP for easy integration to the business' already existing applications, processes, and procedures.
  • Python Scripting was utilized for some of the data feeds where an API web connection to PowerBI could not be established.

Nike WHQ Depot Dedicated Technician / IT Tech Support

2017 - 2020

Stefanini/Nike, Beaverton, Oregon

  • Fostered seamless collaboration with EUS engineers, field technicians, and team administrators to deliver exceptional hardware and software support to onsite clients, ensuring uninterrupted business operations and customer satisfaction.
  • Demonstrated expertise in diagnosing and troubleshooting hardware and software issues promptly, minimizing downtime and maximizing productivity.
  • Streamlined workstation setups by efficiently configuring hardware, devices, and software, enabling employees to optimize their work performance and contribute to business success.
  • Orchestrated the central imaging lab for Nike North America, ensuring consistent and reliable configuration and deployment of computer images across the region, enhancing operational efficiency and maintaining brand standards.
  • Served as a valuable link between the IT procurement team and end-users/team administrators, effectively managing communication, coordinating equipment procurement timelines, and ensuring smooth delivery and deployment processes, contributing to cost control and efficient resource allocation.