● Improved productivity by creating platforms to deliver reliable realtime front-end app data to different teams (product, data analytics, MLEs) for their different data processes.● Reduced operational errors and improved data quality by designing, developing, validating, and maintaining multiple ETL pipelines using SQL, Scala, Databricks, Airflow, Kibana, Jenkins, Datadog, and AWS.● Reduced teams’ response times by maintaining and meeting SLAs for different datasets ensuring predictable, reliable data availability.● Improved core app latency by leading a project to migrate data architecture from monolithic architecture to a more robust microservice architecture in Ruby for event logging.● Implemented image-based search and improved search recommendations latency by researching, configuring, and load-testing vector database (Milvus).● Work cross-functionally with different stakeholders (analytics, engineering, PMs, etc.) to set expectations, clarify requirements and establish timelines for instrumentation and data pipeline creation for products including SmartAI List, Consignment, etc.

● Brainstorm data architecture design and create tasks to appropriately scope project timelines and work to align with business and technical stakeholders.● Create, maintain, and perform on-call support for multiple ETL pipelines using Python, SQL, AWS(Elasticache, DynamoDB, SSM, S3, Athena, ECR, Batch, Lambda, Glue, CodeBuild, CodePipeline), Docker,Terraform, and Make.● Improve team & company engineering efficiency and overall code quality by leading and refining onboarding processes, participating in peer code reviews, and supporting data science and other engineering teams.● Research, identify, and lead initiatives to use new tools & features to optimize data pipelines and increase engineering efficiency, including transitioning our artifact repository tool from CodeArtifact to JFrog.● Bring best talent to company by participating in interview process of data science & data platform teams.

• Reduced data pipeline runtime by ~20% (~2 hours) and overall DB disk usage space by ~5% (~250GB) by optimizing Redshift SQL code in production for multiple pipelines• Automated and reduced runtime of monthly GDPR/CCPA data anonymization process from 30+ hours to 4 hrs which touches ~1 TB of data using Spark, Step Functions, Glue, Spectrum, S3, and Scala.• Created and maintained data pipelines using CI/CD, AWS services (Data Pipeline, CloudFormation, SNS, Lambda, EMR, Redshift, DynamoDB, SSM), Python and Bash to alert the team of issues, create backups, and delete and update data for compliance purposes

• Reduced fatal complications in patient recovery of brain surgery and decreased hospital costs by developing an end-to-end 3D image segmentation pipeline using 3D Convolutional Neural Networks (CNN) to allow physicians to measure volume of brain ventricles.• Beat existing alternative software performance while achieving 86% performance using novel techniques in the field; publications of results are in progress.• Earned a Wicklow AI in Medicine Research Initiative scholarship and presented brain segmentation process and results to technical and non-technical audiences multiple times.• Created ETL pipeline used by multiple NLP projects through automation of medical note deidentification and data integrity verification using Python and Bash scripts.• Classified smoking status of patients using clinical notes using CNN and Recurrent Neural Network (RNN) models for smoking cessation initiative.

• Designed and developed desktop and web applications for use as curriculum using C++, C# (Console, WinForms, MonoGame), and SQL.• Generated new revenue for the company by creating over 20 hours of curriculum content, making an internal wiki, and training multiple instructors on the newly created content.

• Designed and maintained child themes of Wordpress websites in a team of 4 interns• Redesigned the company website in a team of 4 interns and designed the company logo used on Twitter• Led a team of 4 interns to design and program custom websites to customer satisfaction

• Investigated and resolved over 300 clients’ A/R issues on a monthly basis via phone & email• Fixed accounting errors from other users of accounting/billing systems such as CMS & Serengeti• Created, edited, scanned, and filed prebills, bills, and general ledger accounting reports to lawyers’ & clients’ specifications in demanding, fast-paced environment in a timely manner

• Maintained, modified and expanded the data of Intelebill database of over 100K accounts daily • Processed an average of $10K in A/R transactions per day and posted to general ledger via Intelebill • Performed deposits and bank reconciliations daily; assisted with aging reports, invoicing, and monthly statements; maintained and disposed of financial information