Work Experience

International Flavors & Fragrances, Inc

Scientist I

neered data solutions to optimize high-throughput screening workflows in chemistry R&D, improving efficiency by 20% and ensuring accurate, structured data collection for chemical experiments Developed scalable database architectures to process 1M+ experimental data points from diverse chemical experiments, ensuring efficient data storage, retrieval, and integrity enhancing data accessibility for cross-functional teams Automated 80% of data pipelines, reducing manual intervention and accelerating data processing by 30% Built and deployed web applications for real-time data analysis, improving data reporting efficiency for R&D by 40%

Getinge

Data Engineer

Azure Data Engineer at Getinge a medical device manufacturing company. Orchestrating an end-to-end data ingestion and transformation using Rest APIs, Azure Databricks with Medallion architecture, and ADLS Gen 2, optimizing workflows for efficient creation of vector embeddings fed into a chatbot system leveraging LLMs. Designed asynchronous API request calls with a rate-limiting mechanism using a Token bucket algorithm. Building and maintaining robust data pipelines in Azure Synapse, ensuring seamless data ingestion from diverse on-prem source systems into Data Lake and PostgreSQL ensuring data quality standards.Orchestrating an end-to-end data ingestion and transformation using Rest APIs, Azure Databricks with Medallion architecture, and ADLS Gen 2, optimizing workflows for efficient creation of vector embeddings fed into a chatbot system leveraging LLMs. Designed asynchronous API request calls with a rate-limiting mechanism using a Token bucket algorithm.

MVP Lab SDSU

Research Associate: Machine Learning Engineer

Enhanced an AI-based real estate service at Computer Vision Lab SDSU to rate 1.2 million housing communities in San Diego. Automated and accelerated the collection of Google Street View data by 40% using Selenium, Python, and OpenCV for efficient preprocessing. Trained a YOLOv8 model on custom data to detect roadways, utilized Segment Anything Model by Meta to segment YOLOv8 model’s detection reducing the segmentation time by 55%. Applied pre-trained VGG16 for feature extraction, Principal Component Analysis for dimensionality reduction, and KMeans clustering to cluster and rate image data into ten distinct groups based on the extracted features. Performed 3D cluster analysis using Seaborn and Plotly.js Analyzed Elbow graph to find the optimal value for K and calculated Silhouette score for each cluster to find the quality of the cluster.

LifeBand LLC

Software Engineer Intern

Orchestrated a 40% reduction in daily data processing time by efficient data ingestion through Airflow DAGs for a robust 3NF-compliant database schema, ensuring data integrity in collaboration with the cross-functional teams. Designed and Developed REST APIs using the Django-Rest framework and PostgreSQL database, ensuring seamless and robust data interaction for optimal system performance Spearheaded the implementation of streamlined software development processes with BitBucket CI/CD, resulting in a 50% reduction in deployment time

Infosys LTD

Data Engineer

Achieved 75% improvement in data transfer efficiency by orchestrating and implementing a high-throughput data ingestion pipeline using Kafka streaming, enhancing the data storage speed in Snowflake Developed Python scripts to optimize data retrieval from REST APIs, increasing the pipeline's data source efficiency Implemented Airflow for job scheduling, achieving 30% manual work reduction and automated, timely data processing