Anuj Masson

• Spearheaded the design and execution of custom backend solutions utilizing AWS services to process and store unstructured or semi-structured data efficiently.
• Led a multidisciplinary team in crafting data pipelines for various projects, specializing in data ingestion, extraction, and advanced processing methodologies, including Natural Language Processing (NLP).
• Collaborated seamlessly with cross-functional teams to comprehensively grasp business requirements, delivering scalable solutions tailored precisely to meet client needs.

HA Query: A Dashboard for Predicting Health Authority Queries

• Led the end-to-end execution of the project, conceptualizing and implementing the backend architecture.
• Engineered the backend infrastructure to process unstructured data, enriching the Vector database and Knowledge Graph (KG) to power the Dashboard effectively.

Trial AI: Library Management System

• Architected and implemented a robust backend infrastructure for an AWS-based Ontology Management System.
• Leveraged a variety of AWS services including EKS, AWS Batch, Kafka RDS, S3, ElasticSearch, and D-graph to create a resilient multi-tenant architecture.

Digitized Response to RFP Documents:

• Reduced manual effort and time consumption in rewriting proposals by implementing digitization techniques.
• Real-time access to critical information streamlined response creation, optimizing overall duration for similar projects.
• Automation of processes led to substantial cost savings by minimizing administrative overheads and resource utilization.
• Enhanced accessibility allowed users to engage with documents anytime, fostering flexibility and global reach.
• Leveraged digital platforms for robust analytical capabilities, facilitating data extraction and trend analysis for informed decision-making.

Knowledge Engineering Platform (KEP):

• Utilized numerous research documents to enrich knowledge graphs, powering drug research and development.
• Reduced manual efforts by 36 weeks through efficient digitization processes.

Trials AI (Artificial Intelligence):

• Expedited clinical document creation by digitizing, automating, and infusing intelligence into the process.
• Leveraged state-of-the-art artificial intelligence, including Natural Language Processing (NLP) and Large Language Models, to optimize clinical trial protocols.
• Extracted and connected information from clinical study documents using NLP and graph technology.
• Significantly reduced manual intervention by leveraging automation techniques.

Multi-Channel Marketing (MCM):

• Designed and implemented a backend processing pipeline to power dashboards for insightful analysis of marketing channels.
• Enabled identification of the most efficient marketing channels through data-driven insights.

Engineered AWS Data Ingestion Pipelines and REST APIs for internal e-commerce operations serving one of the world's top five pharmaceutical companies:

• Designed and implemented end-to-end AWS solutions for data ingestion pipelines, encompassing preprocessing, shaping, and data storage utilizing SNS topics, AWS Glue, S3 buckets, AWS Lambda, Event Triggers, and DynamoDB.
• Developed REST APIs using AWS API Gateway to facilitate data querying and visualization for feature teams.
• Received recognition for project excellence, including coverage on BBC and awards such as the "Project Champions Award" and "Innovation of the Year Award."

Designed and implemented Satellite Ground Station Monitoring Dashboard:

• Developed user-friendly dashboard enabling real-time monitoring of ground station health.
• Provided comprehensive statistics on user numbers and coverage areas for each ground station.
• Enabled firmware updates for ground stations with single-click functionality.
• Delivered real-time status updates on satellite coverage areas.
• Utilized Python 3 to develop backend infrastructure.