Jatin is a seasoned AI/ML Engineer with 10+ years of industry expertise building innovative enterprise data solutions leveraging both cloud and on-prem technologies. He is a self-starter with great communication skills, a solid understanding of AI, Data Science, advanced statistics, Machine Learning, data mining, and visualization techniques. Jatin creates and maintains new data pipelines on projects using data at scale, implementing critical ETL pipelines, and advancing best practices in a fast-paced, collaborative, inclusive, and iterative delivery environment.
Delivered data warehouse and ETL solutions as part of an agile team using advanced machine learning techniques to improve performance and processes.
Designed and maintained scalable data pipelines using Python, PySpark, Apache Spark, and Databricks to process large datasets reliably and efficiently.
Built cloud-native data workflows on AWS using S3, Lambda, EMR/EMR Serverless, Step Functions, and CloudWatch.
Built and improved infrastructure, application and performance development and ensures tight security including data encryption, security groups, and environment scanning.
Developed clean, maintainable Python applications supported by unit, integration, and automated testing using PyTest.
Implemented CI/CD and GitOps workflows to automate infrastructure provisioning, application testing, and production deployments.
Provisioned and monitored cloud data infrastructure, improving platform reliability, operational visibility, and cost efficiency.
Optimized Spark jobs and data-processing architectures through partitioning, caching, resource tuning, and efficient data-storage strategies.
Designed data models and integrated relational and NoSQL systems, including PostgreSQL, Elasticsearch, and MongoDB.
Built new data pipelines and machine learning models to preprocess and transform massive amounts of structured and unstructured data on NestReady's digital platform.
Set up Big Data Infrastructure (Hadoop) from the ground up with features for monitoring, maintenance, and enhancements of Spark Clusters on the platform.
Improved user click-through rate by 30% and implemented a user personalization feature with a recommendation engine using Locality Sensitive Hashing in Spark ML.
Work as a technical Advisor to early-stage AI startups; contributing to all aspects of the development process and incorporating standards and best practices into engineering solutions.
Mentor software engineers within Next AI ventures; developing re-usable frameworks and reviewing design and code produced by other engineers.
Provide expert-level advice to data scientists, data engineers, and operations for the delivery of high-quality solutions on projects.
Designed, built and deployed systems and tools for the implementation of multiple data pipelines solutions for AI-driven projects within American Express.
Collaborated with and supported data scientists on projects to define new requirements for a Recommendation Engine, NLP Chatbot, and Robotic Process Automation solutions.
Worked effectively within American Express' AI/ML team and mentored junior members on projects.
Developed innovative personalized search results solutions using Spark, Mongo, LSH, AWS S3. It comes with 1+ billion records loaded into the data frame, uses behavioural logs to find similar items. The code was built with Spark ML framework and can run on AWS EMR cluster or GCP's Dataprocs.
Worked on an NLP chatbot for American Express; handling the deployment of the AskGSM platform to respond to queries from external vendor partners and in-house stakeholders on the status of invoices submitted.
NestReady is an innovative machine learning and AI-based platform that places lenders at the centre of the home buying experience. Led processes to reduce customer bounce rate (20%) by generating high-quality custom descriptions of a product using Text Generation algorithms. Enhanced customer experience by building a deep learning-based Super-Resolution model (GAN) to enhance the quality and resolution of house images (Tensorflow) on the platform. Built Customer Buying Intent Generator using customer behavioural and demographic data (K-Means Clustering and Classification).
