Trisha Lalit

Research Assistant - Data Scientist & Information Security Specialist at Boston University

Engineered predictive models analyzing over 100,000 data points from 15 US cities, incorporating environmental factors such as temperature, humidity, and wind speed to improve forecasting accuracy by 30%. Developed ETL pipelines to preprocess and transform large-scale weather datasets, ensuring data integrity, compliance, and efficient ingestion for downstream analytics. Integrated LLM-based analytical modules and API endpoints using Python and AWS Lambda to enable real-time AI model inference and deployment.

Software Engineer at Accenture India

Architected and deployed Java Spring Boot microservices in AWS, processing 300K+ healthcare records, reducing operational costs by 25% while ensuring high system availability. Designed and deployed RESTful APIs with CI/CD pipelines, utilizing Jenkins, Docker, and Kubernetes, resulting in a 50% reduction in deployment cycles and enhanced system reliability. Optimized multi-threaded data ingestion using Apache Spark, enabling scalable analytics for patient data, maintaining 99.9% system uptime. Deployed Dockerized ML microservices and integrated AI-powered modules via REST APIs, aligning with MLOps practices for scalable cloud-based AI applications. Automated cloud resource provisioning and infrastructure management using Python, Ansible, and Terraform, accelerating deployment speed by 50% while enhancing resource utilization and system scalability.

Data Analyst at Intellipaat

Developed CRM automation modules in Python and JavaScript, optimizing lead management workflows, resulting in a 15% improvement in efficiency. Designed and implemented real-time data dashboards using AWS QuickSight, providing marketing teams with actionable insights for sales analytics.