JOSEPHINE PACKIARAJ

• Led end-to-end project delivery for clinical trial data management eTMF systems, coordinating efforts of global, cross-functional team of 50+ members to ensure timely and successful project outcomes.
• Manage capital budget and resources for high-stakes, large-scale projects valued at over $5 billion in total project cost.
• Drove integration of AI technologies into clinical data workflows, automating data ingestion, cleaning, and predictive validation, including integration of GenAI in clinical trial website and chatbots.
• Oversaw GxP and regulatory compliance across software development lifecycles, ensuring adherence to global life sciences standards and minimising risk of non-compliance.
• Enforced information security controls by aligning technical architecture with ISO/IEC 27001 compliance standards, protecting sensitive clinical patient data from potential breaches.

Tech Stack: Python, AI/ML Pipelines, Clinical Trial Data Systems, ISO 42001 (AIMS), ISO 27001, GxP Compliance, Cloud Architecture

• Drive agile project management for Python microservices handling 50M+ daily travel searches across 200+ destinations
• Managed end-to-end delivery of travel data processing pipeline, integrating GDS systems (Amadeus, Sabre, Travelport) and ensuring hotel data accuracy across various vendors
• Coordinated stakeholder communications with airline partners, hotel chains, and travel agencies to ensure compliance with NDC standards and manage risks effectively
• Oversaw technical architecture for scalable Python infrastructure, managed deployment strategies using containerized microservices, and tracked metrics to evaluate platform performance
• Lead Python development project for flight sector mapping and hotel data cleanup platform managing 25-30 team members
• Facilitated AI-assisted development practices using Claude AI and CodeRabbit to improve code review and development efficiency
• Drive Agentic AI Automation for enhanced quality of the system
• Ensured compliance with Payment Card Industry Data Security Standard (PCI DSS) for data protection related to credit card usage

Tech Stack: Python (FastAPI, Django), Microservices, Apache Kafka, Redis, PostgreSQL, Docker, Kubernetes, Azure, GDS Integration

• Led machine learning forecasting project for supply chain demand prediction managing 15+ stakeholders
• Managed cross-functional teams (data scientists, ML engineers, business analysts, DevOps) for development and implementation of ML forecasting algorithms, including LightGBM
• Coordinated ML model development lifecycle including data pipelines, feature engineering, training, validation, and deployment
• Facilitated agile project management with sprint planning and scrum ceremonies ensuring 95%+ forecast accuracy SLA
• Led strategic planning for integration of Python-based ML automation framework with existing supply chain systems to enhance forecasting capabilities
• Oversaw model governance activities, ensuring compliance with bias testing, explainability requirements, and regulatory validation standards

Tech Stack: Python, Machine Learning (TensorFlow, Scikit-learn), CI/CD

• Developed and implemented Natural Language Processing (NLP) solutions to analyze large-scale Verizon network data for customer segmentation and group diversification.

• Led data analysis initiatives to identify customer behavior patterns and improve service personalization using machine learning techniques.

Tech Stack: Python, NLP, Robot Framework, Network Protocols,

• Developed and executed test cases using Python and Pytest for routing protocols on Cisco devices, contributing to robust product validation.
• Automated L3 testing for IPSec, BGP, ISIS, OSPF, and QoS protocols on ASR devices
• Conducted thorough testing on Cisco devices to ensure reliability and performance of networking protocols.

Collaborated in agile development environment, actively participating in scrum practices and sprint cycles to deliver features effectively.

• Collaborated in agile development environment, adhering to scrum practices and managing sprint cycles
• Executed manual and automation testing for Routing/Switching (L2, L3) and NMS/EMS (L7) systems
• Conducted comprehensive testing on Cisco devices to ensure functionality and reliability
• Tested HP storage and network devices including SAP HANA and HPN systems