Walmart

Senior Software Development Engineer Machine Learning 

Working towards saving Sam's Club over $200M dollars a year by using Fraud Detection services.

* Design and develop micro services, REST API's using Python and Flask framework to identify fraudulent users among Sam's club transactions(Dotcom, Returns, SnG, Fuel) in real-time. 
* Owned fraud engine application for dotcom which does 15B USD yearly revenue every year which prevented 46M USD worth of fraud last year. 
* Designed and lead the effort in developing the microservice for Returns Fraud Engine and owns it. It has  prevented 20M USD worth of fraud last year. 
* Design and build distributed data solutions using Cassandra data modeling,  for real time model serving.
* Design, build large-scale data processing pipelines and run nightly batch jobs and event-streaming  using Spark, Kafka and GCP’s Dataproc as well as developed dashboards to monitor the data quality and infrastructure metrics.
* Leveraged robust python multithreading for I/O operations(database calls, external api’s) and multiprocessing for cpu bound operations and reduced the latency of request by 50%. 
* Developed dependency identifying tool which helped in scheduling data engineering jobs in an optimized way(identifies the order and concurrently executable scripts and more). By leveraging the features of tool and ephemeral clusters, able to reduce cost and improve performance of data engineering jobs by allocating clod resources only at the time when required/code refactoring/selecting optimal machine configurations for jobs. Run time of jobs has been reduced from 22 hours to 10 hours which in turn reduced the cost of using Dataproc clusters by 50%.
* Developed optimized code and created dashboards to automate the monitoring of machine learning models performance (data drift, feature drift, performance metrics, integrity issues and more). 

Skills Utilized: Python, Pyspark, Cassandra, Jenkins, Docker, Kubernetes, Kafka, Hadoop, Ensemble Machine Learning

Software Engineer III, Machine learning

BrightEdge

Software Development Engineer

The Ronnie K. Irani Center for the Creation of Economic Wealth (I-CCEW)

•	Analyze business requirements and translate them into the low-level design or custom programs using React and Python. 
•	Designed and built REST API's services that delivered high performance in assessing personal well-being. 
•	Developed REST-based APIs to handle the incoming client requests and involved in coding for models and controllers.
•	Technologies: Git, Flask, Python, REST, React, MS SQL, and MySQL.

Software Engineer Intern

University of Oklahoma

Worked with Aerospace and mechanical department to develop CBDS platform (creates the best design for manufacturing a tool)
* Developed Cloud based decision support platform for design engineers by developing REST API's using Python and Flask framework. 
* Developed Robust python scripts to modify the fortran code files with given input.
* Developed an efficient algorithm to retain the order of execution of jobs and reduced the latency from 3s to 1s.

Skills: Python, Flask, Git, MySQL, GCP

Graduate Research Assistant ( Python Developer)

Tata Consultancy Services

•	Understanding the functional requirements from the business requirement documents provided by the client. 
•	Implemented RESTful web services with Spring MVC and created REST-based controllers to handle the incoming requests. 
•	Created test cases using the unit testing framework, JUnit as part of Test-Driven Development (TDD).
•	Collaborated on the automation framework and increased the quality of the product. 
•	Technologies: Java, Python, Git, Selenium, My SQL, Eclipse.

Software Developer

I am passionate about problem-solving and coding.  

I have 5 years experience in developing scalable and reliable ML training pipelines, backend services and data engineering pipelines.  I’m fascinated by learning new technologies.

At Walmart, I primarily work as an ML Engineer focusing on developing microservices, api's, async processing, data engineering pipelines, building models, automating the model training pipelines. deploying and monitoring the machine learning risk models. 

Key strengths and expertise include:
Python, Cassandra, Kafka, PySpark, Spark, Docker, and GCP.

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