Daniel – Python, React, Django

This is an AI-powered instant calibration identification software. It integrates vehicle diagnostic data, calibration requirements, and advanced workflow automation into a single, user-friendly platform. The platform is tailored for automotive repair shops, OEM calibration specialists, and insurance claims adjusters.

• Developed and transitioned machine learning software into a modern web application, integrating Django, Flask, and PostgreSQL to replace a legacy CSV-based workflow.
• Designed and optimized a PostgreSQL database schema, migrating datasets by implementing Django ORM and ensuring efficient query performance.
• Built and maintained Django REST Framework APIs, enabling seamless data updates between ML models and the database.
• Developed Flask-based microservices to support AWS App Runner deployments, replacing legacy EC2-based architectures for scalability and efficiency.
• Automated CI/CD pipelines with GitHub Actions and Jenkins, deploying containers via AWS ECR and App Runner for streamlined DevOps workflows.
• Enhanced front-end data management by building a dashboard with Bootstrap, DataTables, and vanilla JavaScript, allowing real-time data edits and corrections.
• Implemented secure authentication and API integrations, integrating OAuth, token-based authentication, and third-party APIs like AllData and iCar.
• Refactored and modernized codebases, migrating from local caching to S3 storage and improving observability with CloudWatch logs, Slack alerts, and Django admin tools.
• Improved ML model accuracy by feeding user-validated corrections from the dashboard back into the prediction pipeline, enhancing data integrity.

MVP provides medical practices with analytic software data consolidation tools and web-based visualizations that simplify understanding the business’ performance trends within one single multi-purpose dashboard from a variety of applications in order to streamline the decision-making process for optometry clinics.

• Developed and maintained a Django-based financial analytics platform, integrating QuickBooks and Google Drive for automated KPI tracking.
• Designed and optimized PostgreSQL database models to ensure accurate data storage and retrieval for financial reports.
• Implemented background task processing to automatically detect, process, and update key financial documents in Google Drive.
• Enhanced data integrity and validation by refining PDF-to-database extraction pipelines, ensuring KPIs were correctly parsed and reflected in Google Sheets.
• Built an interactive dashboard with Chart.js, dynamically visualizing financial performance metrics for data-driven decision-making.
• Developed custom API endpoints to facilitate secure data synchronization across the system.
• Worked 1-on-1 with the CEO to deliver project milestones, ensuring the prototype was aligned with business objectives.

The platform's main goal is to enhance an individual’s mental health by providing on-demand support from a clinically trained empathic AI system focused on emotional exploration of the root causes of distress and suffering.

• Designed, developed, and deployed an MVP for a digital therapeutic AI assistant using OpenAI’s API and Langchain.
• Fine-tuned GPT-4 with a custom training set to create an Empathic AI model for guiding users through therapeutic exercises.
• Built the backend using Django Rest Framework, integrating with a ReactJS frontend and implementing Auth0 authentication with social logins and passwordless access.
• Designed the backend architecture following hexagonal architecture and domain-driven design principles.
• Developed and launched the company website, implementing a Django Rest Framework/React stack with TypeScript.
• Automated CI/CD pipelines using GitHub Actions and deployed with Google Cloud Build and Google Cloud Run.
• Installed Sentry for error monitoring with Slack notifications for real-time issue tracking.
• Managed Google Analytics, Google Tag Manager, and SEO optimizations, improving digital reach and user engagement.
• Created and executed Google Ad campaigns, driving targeted traffic to the platform.

Software designed to automate the tip distribution process for restaurants, facilitating nightly or weekly tip-outs.

• Designed, developed, and tested API endpoints for a Tip Calculator project, automating tip-out calculations for restaurants.
• Built and maintained a FastAPI/Vue/PostgreSQL stack within a microservices architecture, ensuring scalability and efficiency.
• Integrated with multiple POS (Point of Sale) APIs, enabling real-time synchronization of hospitality industry transaction data.
• Developed and managed Dockerized environments, streamlining DevOps workflows and deployment processes.
• Implemented a subscription and invoicing system using Stripe’s API, automating billing and payments.
• Provided training for Sales and Marketing teams, ensuring smooth onboarding and operational understanding of the new system.
• Collaborated with Client Services and Sales to introduce the product to new and existing clients, demonstrating its impact on bookkeeping efficiency.
• Designed and developed Vue components for a public-facing application, improving user experience and interactivity.
• Created and maintained SendGrid email templates and campaigns, optimizing communication and engagement.

Internal platform tailored for analytics and video access, catering to players, coaches, and scouts within an NHL team.

• Designed, developed, and maintained tools within TML’s Django-based platform, enhancing data accessibility and usability.
• Worked on ingesting and processing player tracking data, scouting reports, and video to generate actionable insights.
• Transformed NHL, Sportlogiq, and optical tracking data into meaningful metrics and visual presentations.
• Worked on downloading and segmenting game-length video into play-by-play clips, linking them to corresponding event data.
• Developed algorithms to extract valuable insights from large datasets, including new computer vision-based play-by-play analysis.
• Built interactive tools that enable coaches, analysts, and staff to explore, visualize, and manipulate hockey data.
• Managed background job processing with Celery on Heroku, ensuring efficient data updates and automation.
• Wrote and executed unit tests in Django, improving code reliability and system stability.
• Configured and maintained cloud infrastructure on Heroku and AWS, optimizing performance and scalability.
• Collaborated with non-technical stakeholders, ensuring data-driven insights are accessible and actionable.
• Analyzed hockey data and presented insights to enhance decision-making across the organization.
• Contributed to research projects, applying advanced data processing techniques to improve player and team performance analysis.