Engineer Data

Akhil Madamala

adi87q@r.postjobfree.com • +1-480-***-**** • www.linkedin.com/in/akhil-madamala

EDUCATION

Masters, Computer Science: May 2020

Arizona State University, Tempe, AZ

• Coursework: Multimedia and Web databases, Data Mining, Data Visualization, Distributed Database Systems, Software Project/Process/Quality Management, Semantic Web Mining etc. Bachelors of Technology, Computer Science: May 2018 Vellore Institute of Technology, Vellore, TN, India

• Coursework: Soft Computing, Image & vision, Object-Oriented Programming, Web Programming, Data structures, etc. TECHNICAL SKILLS

• Programming Languages : Python, Java, C++.

• Databases and tools : MySQL, Tableau, AWS(EC2,Lambda, EMR, s3 etc.), PySpark, Jenkins, Hadoop, Kafka, Cassandra, Git, Bash.

• Web technologies : HTML, Java Script(D3.js,vanilla JS), CSS.

• Frameworks : Flask, Django, Spring Boot.

CERTIFICATIONS

• AWS Solutions Architect: Associate 2020

• AWS certified: Big Data specialty 2020

COMPETITIONS ON KAGGLE

• Scored in Top 5 % in Titanic Machine learning from Disaster.

• Scored in Top 10 % in House price prediction.

PROFESSIONAL EXPERIENCE

American Express: Machine learning engineer June 2020 –Current

• Worked on Building a Personalized Precision based Modelling Pipeline for customers in United States.

• Built a Spark based ETL pipeline for preprocessing the customer data and obtained features.

• Filtered the features based on Embedded methods and Feature Engineered them.

• Helped to Tune, evaluate the model and deploy in a large-scale distributed environment on AWS.

• Also, monitored the metrics like Gini drop, PSI etc. to identify model drift and evaluate the model. Arizona state university: Software Development Engineer Sep 2018 – June 2020

• Built a Regression model with a Neural Network to predict the protein properties based on generated features that capture the environment.

• Engineered the features after conducting Exploratory analysis and by Clustering. Later, reduced the dimensionality of 10 million data points for reduction of Noise, better prediction, and faster training.

• Worked on building a modified multi-layered neural network from scratch and evaluated performance using adjusted R2 and RMSLE metrics on a High-performance cluster (HPC).

• Built an End to End real time analytics pipeline using Kinesis, Spark, and Cassandra.

• Worked on the performance testing and unit testing for the Rest service built in Django. ACADEMIC PROJECTS & HACKATHONS

Real Time Product Recommendation System: (ASU)May-July 2020

• Built a Recommendation model based on Customer purchase data.

• Built a data pipeline using Amazon Kinesis firehose and stored the data lake in Amazon S3.

• Used Glue as a meta store for producing the schema for the pipeline.

• Later used Transient Elastic Map Reduce to give recommendation to users. Job posts classifier: (ASU) Jan-May 2020

• Scraped data from indeed job postings using beautiful soup to train an NLP Classification model.

• Pre-processed data by removing stop words, punctuation, noise, etc.

• Achieved a cross-validation score of 86 percent by Random search.

• Classified data scraped per company to respective functional areas using the trained model. Movie Recommendation System: (ASU) Aug-Dec 2019

• Created a Recommendation model to suggest products to users and boost sales.

• Trained the model using matrix factorization and content-based filtering to predict the user and movie vectors.

• Tuned parameters using random search and evaluated the model with other trained models using RMSE values.

• Displayed the analytics using Sunburst, Word cloud and Bubble chart using D3.js interactive visualizations.

• Managed the website using Spring Boot and hosted it on AWS.

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