Peer Reviewer

 Lead a high-performing team of Data Scientists & ML engineers to develop and deploy AI/ML solutions across Intel's manufacturing and supply chain operations. Spearheaded the development of a Retrieval-Augmented Generation (RAG) based chatbot, significantly enhancing the productivity of Corporate ,planning & logistics organization by automating document analysis. Architected & led the creation of a deep learning-based computer vision system that improved logistics efficiency and led to $14M in cost savings for Intel’s warehouses. Published and presented advanced analytics research, including a novel warpage analysis tool that optimized semiconductor manufacturing processes. Recognized for driving innovation and delivering strategic AI/ML solutions that align with business objectives.

•Built a multivariate Linear Regression model (with 85% accuracy) as well as operationalized the model in Greenplum MPP platform to predict and visualize on-time delivery metric of Suppliers. This solution processes, transforms and predicts on 10 GB of data weekly. This has improved assembly/shop inventory, supplier OTD performance & $10M to $15M yearly savings for business.•Built a Gradient Boosting ensembled model for predicting Asset Allocations for a key customer of predix. This model is built on GE Predix Analytic Catalog. This has made GE Predix compelling for the customer for building and deploying Machine Learning algorithms•Delivered 11 analytic microservices onto Predix Analytics catalog (11 out of 100, top contributor in PDS team). This supported positioning Predix as a top Analytic IIOT Platform in Forrester report and helped to make Predix more compelling to Toshiba, Schindler & Sun Power (https://www.predix.io/catalog/analytics). Some of the key Analytics built:¬Density Based clustering¬MeanShift Clustering¬Categorical to numerical data¬Max Variance feature Analysis¬Linear Discriminant Analysis ¬Random Forrest Classifier¬Gradient Boosting Classifier¬Ensembled Classifier¬Isotonic Regression•Built ETL infrastructure which purges and loads 140 GB of network & OPS data every week. Developed ETL infrastructure for structured & unstructured data for network, machine health, incidents & CI data enabling IT operations business to better support mission critical applications •Engineered unstructured outage data /historical weather data to enable predictive model around outages. Engineered Power outage alerts on twitter data. GE Energy quoted "Perfect social analytics use case implemented"•Built a Python framework for GE Healthcare to engineer Install Base config data to identify potential upgrade opportunities with a potential revenue impact of $8MM/yearlyEnv: Python, Sklearn, SQL, Talend, Greenplum, Java, Shell Scripting, Hadoop – HDFS, HIVE

Hightail is a Cloud file sharing/storage midsize company. I am responsible to provide key KPIs, sales leads to the Sales/Finance team as well as to the key Stake holders. I have designed a robust, scalable Datawarehouse platform to suffice the tableau dashboards as well as the adhoc reporting needs from multiple sources which includes legacy OLTP and NoSQL systemsSkillset: Amazon S3, Amazon Redshift, SQL, JIRA, Talend, Sqlserver, PostgreSQL, SSIS, SSRS, Java

Skillset: Hadoop, Hive, Python, Unix shell script, PLSQL, Oracle 10g, JIRA, SVN, Pycharm, Perforce Version Control

Skillset: OBIEE , Oracle, Teradata, PL/SQL, Toad, Linux, Informatica 8.6, Oracle Applications – Install Base and Service Agreement, Hadoop – HDFS, Hbase, Map reduce, CDH4

Skillset: Hadoop, Hive, Python, Unix shell script, PLSQL, Oracle , JIRA, SVN, Pycharm, Perforce Version Control

Skillset: OBIEE, Oracle , Teradata, PL/SQL, Toad, Linux, Informatica